{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2d2d6f03",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📂 폴더 분석: /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/train\n",
      "📄 파일 개수: 45623\n",
      "🧮 클래스별 개수:\n",
      "  class  0 (face): 88372\n",
      "  class  1 (shirt (blouse)): 6161\n",
      "  class  2 (t-shirt): 16548\n",
      "  class  3 (sweater): 1494\n",
      "  class  4 (cardigan): 1107\n",
      "  class  5 (jacket): 7833\n",
      "  class  6 (vest): 719\n",
      "  class  7 (pants): 12414\n",
      "  class  8 (shorts): 2756\n",
      "  class  9 (skirt): 5046\n",
      "  class 10 (coat): 3124\n",
      "  class 11 (dress): 18739\n",
      "  class 12 (bag, wallet): 7217\n",
      "\n",
      "📂 폴더 분석: /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/val\n",
      "📄 파일 개수: 1158\n",
      "🧮 클래스별 개수:\n",
      "  class  0 (face): 3539\n",
      "  class  1 (shirt (blouse)): 102\n",
      "  class  2 (t-shirt): 477\n",
      "  class  3 (sweater): 21\n",
      "  class  4 (cardigan): 12\n",
      "  class  5 (jacket): 183\n",
      "  class  6 (vest): 22\n",
      "  class  7 (pants): 314\n",
      "  class  8 (shorts): 106\n",
      "  class  9 (skirt): 162\n",
      "  class 10 (coat): 104\n",
      "  class 11 (dress): 508\n",
      "  class 12 (bag, wallet): 214\n",
      "\n",
      "=====================================\n",
      "📊 전체(train + val) 클래스별 개수\n",
      "=====================================\n",
      "  class  0 (face): 91911\n",
      "  class  1 (shirt (blouse)): 6263\n",
      "  class  2 (t-shirt): 17025\n",
      "  class  3 (sweater): 1515\n",
      "  class  4 (cardigan): 1119\n",
      "  class  5 (jacket): 8016\n",
      "  class  6 (vest): 741\n",
      "  class  7 (pants): 12728\n",
      "  class  8 (shorts): 2862\n",
      "  class  9 (skirt): 5208\n",
      "  class 10 (coat): 3228\n",
      "  class 11 (dress): 19247\n",
      "  class 12 (bag, wallet): 7431\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from collections import defaultdict\n",
    "import yaml\n",
    "\n",
    "# ---------------------------------------\n",
    "# 1) YAML 파일에서 클래스 이름 불러오기\n",
    "# ---------------------------------------\n",
    "yaml_path = \"/home/cuuva/experiment/datasets/fashionpedia_yolo/fashionpedia_custom.yaml\"\n",
    "\n",
    "with open(yaml_path, \"r\") as f:\n",
    "    data = yaml.safe_load(f)\n",
    "\n",
    "names = data[\"names\"]\n",
    "# keys가 문자열일 수도 있음 → 정수 key로 맞춰줌\n",
    "class_names = {int(k): v for k, v in names.items()}\n",
    "\n",
    "# ---------------------------------------\n",
    "# 2) Label 파일 읽어서 클래스별 개수 계산\n",
    "# ---------------------------------------\n",
    "label_root = \"/home/cuuva/experiment/datasets/fashionpedia_yolo/labels\"\n",
    "folders = [\"train\", \"val\"]\n",
    "\n",
    "total_counts = defaultdict(int)\n",
    "\n",
    "for folder in folders:\n",
    "    folder_path = os.path.join(label_root, folder)\n",
    "    class_counts = defaultdict(int)\n",
    "\n",
    "    txt_files = [f for f in os.listdir(folder_path) if f.endswith(\".txt\")]\n",
    "\n",
    "    print(f\"\\n📂 폴더 분석: {folder_path}\")\n",
    "    print(f\"📄 파일 개수: {len(txt_files)}\")\n",
    "\n",
    "    for txt in txt_files:\n",
    "        with open(os.path.join(folder_path, txt), \"r\") as f:\n",
    "            lines = f.readlines()\n",
    "\n",
    "        for line in lines:\n",
    "            class_id = int(line.split()[0])\n",
    "            class_counts[class_id] += 1\n",
    "            total_counts[class_id] += 1\n",
    "\n",
    "    # --- 폴더별 결과 출력 ---\n",
    "    print(\"🧮 클래스별 개수:\")\n",
    "    for cid in sorted(class_counts.keys()):\n",
    "        print(f\"  class {cid:2d} ({class_names.get(cid, 'Unknown')}): {class_counts[cid]}\")\n",
    "\n",
    "# ---------------------------------------\n",
    "# 3) 전체 합산 결과 출력\n",
    "# ---------------------------------------\n",
    "print(\"\\n=====================================\")\n",
    "print(\"📊 전체(train + val) 클래스별 개수\")\n",
    "print(\"=====================================\")\n",
    "for cid in sorted(total_counts.keys()):\n",
    "    print(f\"  class {cid:2d} ({class_names.get(cid, 'Unknown')}): {total_counts[cid]}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2129cfe8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New https://pypi.org/project/ultralytics/8.3.235 available 😃 Update with 'pip install -U ultralytics'\n",
      "Ultralytics 8.3.225 🚀 Python-3.10.18 torch-2.9.1+cu128 CUDA:0 (NVIDIA GeForce RTX 5090, 32109MiB)\n",
      "\u001b[34m\u001b[1mengine/trainer: \u001b[0magnostic_nms=False, amp=True, augment=False, auto_augment=randaugment, batch=-1, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/home/cuuva/experiment/datasets/fashionpedia_yolo/fashionpedia_custom.yaml, degrees=0.0, deterministic=True, device=0, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=500, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.001, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8m.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=yolov8m_fashion+face_nohood, nbs=64, nms=False, opset=None, optimize=False, optimizer=AdamW, overlap_mask=True, patience=50, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=fashionpedia_exp, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion+face_nohood, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=8, workspace=None\n",
      "Overriding model.yaml nc=80 with nc=13\n",
      "\n",
      "                   from  n    params  module                                       arguments                     \n",
      "  0                  -1  1      1392  ultralytics.nn.modules.conv.Conv             [3, 48, 3, 2]                 \n",
      "  1                  -1  1     41664  ultralytics.nn.modules.conv.Conv             [48, 96, 3, 2]                \n",
      "  2                  -1  2    111360  ultralytics.nn.modules.block.C2f             [96, 96, 2, True]             \n",
      "  3                  -1  1    166272  ultralytics.nn.modules.conv.Conv             [96, 192, 3, 2]               \n",
      "  4                  -1  4    813312  ultralytics.nn.modules.block.C2f             [192, 192, 4, True]           \n",
      "  5                  -1  1    664320  ultralytics.nn.modules.conv.Conv             [192, 384, 3, 2]              \n",
      "  6                  -1  4   3248640  ultralytics.nn.modules.block.C2f             [384, 384, 4, True]           \n",
      "  7                  -1  1   1991808  ultralytics.nn.modules.conv.Conv             [384, 576, 3, 2]              \n",
      "  8                  -1  2   3985920  ultralytics.nn.modules.block.C2f             [576, 576, 2, True]           \n",
      "  9                  -1  1    831168  ultralytics.nn.modules.block.SPPF            [576, 576, 5]                 \n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 12                  -1  2   1993728  ultralytics.nn.modules.block.C2f             [960, 384, 2]                 \n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 15                  -1  2    517632  ultralytics.nn.modules.block.C2f             [576, 192, 2]                 \n",
      " 16                  -1  1    332160  ultralytics.nn.modules.conv.Conv             [192, 192, 3, 2]              \n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 18                  -1  2   1846272  ultralytics.nn.modules.block.C2f             [576, 384, 2]                 \n",
      " 19                  -1  1   1327872  ultralytics.nn.modules.conv.Conv             [384, 384, 3, 2]              \n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 21                  -1  2   4207104  ultralytics.nn.modules.block.C2f             [960, 576, 2]                 \n",
      " 22        [15, 18, 21]  1   3783223  ultralytics.nn.modules.head.Detect           [13, [192, 384, 576]]         \n",
      "Model summary: 169 layers, 25,863,847 parameters, 25,863,831 gradients, 79.1 GFLOPs\n",
      "\n",
      "Transferred 469/475 items from pretrained weights\n",
      "Freezing layer 'model.22.dfl.conv.weight'\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 9550.5±5256.6 MB/s, size: 88.2 KB)\n",
      "\u001b[K\u001b[34m\u001b[1mtrain: \u001b[0mScanning /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/train... 45623 images, 76 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 45623/45623 8.8Kit/s 5.2s0.1ss\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/train.cache\n",
      "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n",
      "\u001b[34m\u001b[1mAutoBatch: \u001b[0mComputing optimal batch size for imgsz=640 at 60.0% CUDA memory utilization.\n",
      "\u001b[34m\u001b[1mAutoBatch: \u001b[0mCUDA:0 (NVIDIA GeForce RTX 5090) 31.36G total, 0.25G reserved, 0.24G allocated, 30.87G free\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cuuva/anaconda3/envs/1stagedetect/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Params      GFLOPs  GPU_mem (GB)  forward (ms) backward (ms)                   input                  output\n",
      "    25863847        79.1         2.269         33.99         172.2        (1, 3, 640, 640)                    list\n",
      "    25863847       158.2         3.662         9.859         34.49        (2, 3, 640, 640)                    list\n",
      "    25863847       316.4         4.731         13.43         46.67        (4, 3, 640, 640)                    list\n",
      "    25863847       632.8         7.768         26.11         70.26        (8, 3, 640, 640)                    list\n",
      "    25863847        1266        10.767         26.94         118.4       (16, 3, 640, 640)                    list\n",
      "    25863847        2531        22.039         55.37         244.4       (32, 3, 640, 640)                    list\n",
      "    25863847        5063        41.209         117.2         441.1       (64, 3, 640, 640)                    list\n",
      "\u001b[34m\u001b[1mAutoBatch: \u001b[0mUsing batch-size 27 for CUDA:0 19.11G/31.36G (61%) ✅\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 7599.0±4533.3 MB/s, size: 66.6 KB)\n",
      "\u001b[K\u001b[34m\u001b[1mtrain: \u001b[0mScanning /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/train.cache... 45623 images, 76 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 45623/45623 94.7Mit/s 0.0s\n",
      "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n",
      "\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 3102.9±926.7 MB/s, size: 71.1 KB)\n",
      "\u001b[K\u001b[34m\u001b[1mval: \u001b[0mScanning /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/val... 1158 images, 0 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 1158/1158 6.4Kit/s 0.2s2s\n",
      "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /home/cuuva/experiment/datasets/fashionpedia_yolo/labels/val.cache\n",
      "Plotting labels to /home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion+face_nohood/labels.jpg... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.001, momentum=0.937) with parameter groups 77 weight(decay=0.0), 84 weight(decay=0.000421875), 83 bias(decay=0.0)\n",
      "Image sizes 640 train, 640 val\n",
      "Using 8 dataloader workers\n",
      "Logging results to \u001b[1m/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion+face_nohood\u001b[0m\n",
      "Starting training for 500 epochs...\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      1/500      10.9G     0.8353      1.134      1.129        126        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:56<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.2it/s 2.4s0.1s\n",
      "                   all       1158       5764      0.584      0.383        0.4      0.291\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      2/500      12.4G     0.7803     0.9816      1.099        128        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.5it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.553      0.493      0.492      0.385\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      3/500      12.4G     0.7607     0.9354      1.086        166        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.5it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.683      0.484       0.54      0.423\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      4/500      12.4G     0.7293     0.8818      1.066        107        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.5it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.684      0.522       0.56      0.453\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      5/500      12.5G     0.6926     0.8283      1.046        153        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.4it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.655      0.559       0.61      0.498\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      6/500      12.6G     0.6713     0.7994      1.035        137        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.638      0.589      0.645      0.539\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      7/500      12.6G     0.6537      0.772      1.025        203        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.636      0.635      0.658      0.556\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      8/500      12.7G     0.6412     0.7485      1.019         74        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.5it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.665       0.62      0.657      0.557\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K      9/500      13.9G     0.6266     0.7293      1.013        127        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764       0.69      0.649      0.691      0.589\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     10/500      13.9G     0.6164      0.712      1.005        196        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.659      0.684      0.708      0.603\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     11/500        14G     0.6095     0.7012      1.003        139        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.774      0.632      0.726      0.622\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     12/500      14.1G     0.6004     0.6848     0.9967        142        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.693      0.707      0.719      0.617\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     13/500      14.1G     0.5933     0.6733      0.993        157        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.737      0.691      0.734      0.634\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     14/500      14.2G     0.5857     0.6605       0.99        118        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.737      0.683      0.735      0.635\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     15/500      14.3G     0.5823     0.6515     0.9874        165        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.734      0.694      0.741      0.646\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     16/500      14.3G     0.5773     0.6424      0.984         98        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764       0.74      0.694      0.749      0.651\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     17/500      14.4G     0.5708      0.634     0.9815        139        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.755      0.692      0.756      0.661\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     18/500      14.5G     0.5653      0.623      0.978        140        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:56<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.5it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.747      0.699      0.756      0.661\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     19/500      14.5G     0.5623     0.6184     0.9775        131        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.804      0.672      0.763      0.667\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     20/500      14.6G     0.5597     0.6106     0.9756        136        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.776      0.698      0.768      0.672\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     21/500      15.8G     0.5541     0.5994     0.9695        175        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.767      0.704      0.775      0.677\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     22/500      11.2G     0.5502     0.5956     0.9704        148        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.804      0.691      0.778       0.68\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     23/500        12G     0.5472     0.5893     0.9681        115        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.823      0.685      0.779      0.683\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     24/500      13.1G     0.5429     0.5836     0.9658        150        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.803       0.69      0.781      0.686\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     25/500      13.1G     0.5397     0.5765     0.9641        119        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764       0.77      0.701      0.781      0.687\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     26/500      13.1G     0.5389       0.57     0.9621        186        640: 100% ━━━━━━━━━━━━ 1690/1690 3.9it/s 7:08<0.3s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 7.8it/s 2.8s0.1s\n",
      "                   all       1158       5764      0.739       0.73      0.781      0.687\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     27/500      13.2G     0.5369     0.5665     0.9621        140        640: 100% ━━━━━━━━━━━━ 1690/1690 3.9it/s 7:11<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.722      0.745      0.782      0.688\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     28/500      13.3G     0.5323     0.5596     0.9606        107        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.725      0.745      0.783      0.689\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     29/500      13.4G     0.5309     0.5575      0.958        188        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.739      0.732      0.783      0.689\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     30/500      14.5G     0.5292     0.5538     0.9602        105        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.752       0.72      0.783      0.689\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     31/500      14.6G     0.5261     0.5455     0.9564        118        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764       0.75      0.735      0.784       0.69\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     32/500      14.7G     0.5259     0.5446     0.9566        100        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.746      0.749      0.784       0.69\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     33/500      14.7G     0.5208     0.5397     0.9548        178        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.751       0.75      0.789      0.694\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     34/500      14.8G     0.5193     0.5341     0.9529        112        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.762      0.739      0.791      0.696\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     35/500      14.9G      0.518     0.5313      0.953        160        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.765      0.745      0.792      0.698\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     36/500      14.9G     0.5146     0.5245     0.9515        177        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.765      0.738       0.79      0.697\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     37/500        15G     0.5139     0.5227     0.9508        136        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.2s\n",
      "                   all       1158       5764      0.761      0.744      0.794      0.701\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     38/500      15.1G     0.5114     0.5193     0.9483        169        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.763      0.731      0.796      0.703\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     39/500      15.1G     0.5102     0.5147     0.9481        106        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.789      0.717      0.797      0.704\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     40/500      15.2G     0.5096     0.5142     0.9474        153        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.2s\n",
      "                   all       1158       5764      0.786       0.72      0.797      0.704\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     41/500      15.3G     0.5073     0.5068     0.9458        143        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.772      0.729      0.801      0.707\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     42/500      15.3G     0.5044     0.5037     0.9448        169        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.772       0.73      0.801      0.706\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     43/500      16.5G     0.5033     0.5004     0.9427        139        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764       0.78      0.724        0.8      0.706\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     44/500      11.2G        0.5     0.4998     0.9425        182        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.761      0.738      0.799      0.705\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     45/500      12.3G     0.5013     0.4956     0.9426        127        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764        0.8       0.71        0.8      0.707\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     46/500      13.5G     0.4993     0.4932     0.9416        165        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764       0.77      0.732      0.798      0.705\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     47/500      13.5G     0.4973     0.4924     0.9407        137        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.763      0.741      0.799      0.706\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     48/500      13.6G      0.498     0.4896     0.9414        113        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.4it/s 2.3s0.2s\n",
      "                   all       1158       5764      0.764      0.739      0.798      0.706\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     49/500      13.7G     0.4955     0.4841       0.94        150        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.778      0.739      0.797      0.705\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     50/500      13.7G     0.4937     0.4819     0.9386        129        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.757       0.75      0.798      0.707\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     51/500      13.8G     0.4917     0.4804     0.9376        146        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.753      0.761      0.801       0.71\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     52/500      13.9G     0.4925      0.479     0.9367        111        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.759      0.757      0.799       0.71\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     53/500      13.9G     0.4906     0.4737      0.936        179        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764       0.75      0.758        0.8       0.71\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     54/500        14G     0.4889     0.4725     0.9365        190        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.744      0.766        0.8      0.712\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     55/500      14.1G     0.4868     0.4679     0.9336        135        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764       0.74       0.77        0.8      0.712\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     56/500      14.1G     0.4863     0.4696     0.9336        113        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.751       0.76      0.801      0.712\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     57/500      15.4G     0.4862      0.465     0.9352        117        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:56<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.1s\n",
      "                   all       1158       5764      0.754      0.765      0.799      0.711\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     58/500      15.4G     0.4848     0.4628     0.9332        133        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:50<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.757      0.761      0.799      0.711\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     59/500      15.5G     0.4817     0.4625      0.932        147        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.2s\n",
      "                   all       1158       5764      0.762      0.751      0.798      0.709\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     60/500      15.6G     0.4821     0.4584     0.9313        140        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.768       0.75      0.799       0.71\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     61/500      15.6G     0.4782     0.4548     0.9294        110        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.784      0.738      0.798      0.709\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     62/500      15.7G     0.4804     0.4541     0.9298        178        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.7it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.794      0.733      0.798      0.709\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     63/500      11.2G     0.4779     0.4511     0.9291        187        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s0.2s\n",
      "                   all       1158       5764       0.79      0.738      0.799      0.711\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     64/500      11.2G     0.4781     0.4499      0.929        108        640: 100% ━━━━━━━━━━━━ 1690/1690 4.1it/s 6:51<0.2s\n",
      "\u001b[K                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100% ━━━━━━━━━━━━ 22/22 9.6it/s 2.3s<0.1s\n",
      "                   all       1158       5764      0.801      0.732        0.8      0.714\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "\u001b[K     65/500      11.2G     0.4757     0.4488       0.93        208        640: 28% ━━━───────── 475/1690 4.1it/s 1:56<4:579"
     ]
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "\n",
    "# 1. 모델 로드 (YOLOv8m 사용)\n",
    "model = YOLO('yolov8m.pt')\n",
    "\n",
    "# 2. 학습 실행\n",
    "# 위에서 생성된 yaml 파일 경로를 넣어줍니다.\n",
    "train_results = model.train(\n",
    "    data=\"/home/cuuva/experiment/datasets/fashionpedia_yolo/fashionpedia_custom.yaml\", \n",
    "    epochs=300,            \n",
    "    imgsz=640,\n",
    "    batch=-1,              \n",
    "    device=\"cuda\",\n",
    "    optimizer='AdamW',\n",
    "    lr0=0.001,\n",
    "    patience=50,\n",
    "    project='fashionpedia_exp',\n",
    "    name='yolov8m_fashion+face_nohood',\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fdfe3123",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ultralytics 8.3.225 🚀 Python-3.10.18 torch-2.9.1+cu128 CUDA:0 (NVIDIA GeForce RTX 5090, 32109MiB)\n",
      "Model summary (fused): 92 layers, 25,842,076 parameters, 0 gradients, 78.7 GFLOPs\n",
      "\n",
      "\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from '/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuned_exp/yolov8m_finetuned_4class/weights/best_finetuned_clothes.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 8, 8400) (49.6 MB)\n",
      "\n",
      "\u001b[34m\u001b[1mONNX:\u001b[0m starting export with onnx 1.19.1 opset 20...\n",
      "\u001b[34m\u001b[1mONNX:\u001b[0m slimming with onnxslim 0.1.71...\n",
      "\u001b[34m\u001b[1mONNX:\u001b[0m export success ✅ 0.6s, saved as '/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuned_exp/yolov8m_finetuned_4class/weights/best_finetuned_clothes.onnx' (98.8 MB)\n",
      "\n",
      "Export complete (0.7s)\n",
      "Results saved to \u001b[1m/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuned_exp/yolov8m_finetuned_4class/weights\u001b[0m\n",
      "Predict:         yolo predict task=detect model=/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuned_exp/yolov8m_finetuned_4class/weights/best_finetuned_clothes.onnx imgsz=640  \n",
      "Validate:        yolo val task=detect model=/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuned_exp/yolov8m_finetuned_4class/weights/best_finetuned_clothes.onnx imgsz=640 data=/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuning_dataset.yaml  \n",
      "Visualize:       https://netron.app\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/home/cuuva/git/Detection_Experiment/fashion_yolo/finetuning_exp/finetuned_exp/yolov8m_finetuned_4class/weights/best_finetuned_clothes.onnx'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "model = YOLO(\"/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_noface/weights/best_clothes_detect.pt\")\n",
    "model.export(format=\"onnx\", imgsz=640, device=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "36092edd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "▶ Processing... please wait\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 17.2ms\n",
      "Speed: 0.9ms preprocess, 17.2ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.8ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.7ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 pantss, 6.7ms\n",
      "Speed: 1.1ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.6ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 shirt (blouse)s, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 shirt (blouse)s, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.6ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.6ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.8ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 1.0ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.1ms\n",
      "Speed: 0.5ms preprocess, 7.1ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 1 coat, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 1 coat, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.7ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 shirt (blouse), 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.7ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 1.4ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.8ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.6ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.8ms preprocess, 6.8ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.8ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 1 bag, wallet, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.9ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.8ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.8ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.6ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.8ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.7ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.7ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 7.1ms\n",
      "Speed: 0.8ms preprocess, 7.1ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.7ms\n",
      "Speed: 0.6ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 7.1ms\n",
      "Speed: 0.7ms preprocess, 7.1ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.7ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.8ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.7ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.8ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.8ms preprocess, 6.8ms inference, 1.1ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.6ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 1.7ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 2 pantss, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 t-shirts, 2 pantss, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.8ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 t-shirts, 1 pants, 7.0ms\n",
      "Speed: 0.6ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 t-shirts, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 t-shirts, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 t-shirts, 2 pantss, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.9ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 6.8ms\n",
      "Speed: 0.9ms preprocess, 6.8ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 2 pantss, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.7ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.4ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.9ms\n",
      "Speed: 0.5ms preprocess, 6.9ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.9ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 t-shirts, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 1.0ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.1ms\n",
      "Speed: 0.6ms preprocess, 7.1ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.1ms\n",
      "Speed: 0.5ms preprocess, 7.1ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 1.4ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 1.0ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.8ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.9ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 coat, 7.1ms\n",
      "Speed: 0.5ms preprocess, 7.1ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 2 jackets, 1 coat, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 coat, 7.0ms\n",
      "Speed: 0.5ms preprocess, 7.0ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 coat, 7.0ms\n",
      "Speed: 0.6ms preprocess, 7.0ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 6.9ms\n",
      "Speed: 0.6ms preprocess, 6.9ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.7ms\n",
      "Speed: 0.6ms preprocess, 6.7ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 1 pants, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 pants, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.7ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 6.8ms\n",
      "Speed: 0.6ms preprocess, 6.8ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 7.1ms\n",
      "Speed: 0.4ms preprocess, 7.1ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 pants, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.7ms\n",
      "Speed: 0.8ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 6.7ms\n",
      "Speed: 1.5ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 t-shirt, 1 jacket, 6.8ms\n",
      "Speed: 0.5ms preprocess, 6.8ms inference, 0.6ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 coat, 6.7ms\n",
      "Speed: 1.1ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 6.8ms\n",
      "Speed: 0.4ms preprocess, 6.8ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 7.0ms\n",
      "Speed: 0.4ms preprocess, 7.0ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 1 jacket, 6.7ms\n",
      "Speed: 0.4ms preprocess, 6.7ms inference, 0.5ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 6.7ms\n",
      "Speed: 0.5ms preprocess, 6.7ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "\n",
      "0: 384x640 (no detections), 7.1ms\n",
      "Speed: 0.4ms preprocess, 7.1ms inference, 0.2ms postprocess per image at shape (1, 3, 384, 640)\n",
      "🎉 Done! Saved to: /home/cuuva/다운로드/clothes_detect.mp4\n"
     ]
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "import cv2\n",
    "\n",
    "# 경로 설정\n",
    "video_path = \"/home/cuuva/다운로드/face_recog.MOV\"\n",
    "model_path = \"/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_noface/weights/best_clothes_detect.pt\"\n",
    "output_path = \"/home/cuuva/다운로드/clothes_detect.mp4\"\n",
    "\n",
    "# 모델 로드\n",
    "model = YOLO(model_path)\n",
    "\n",
    "# 비디오 읽기\n",
    "cap = cv2.VideoCapture(video_path)\n",
    "\n",
    "# 비디오 설정 정보 가져오기\n",
    "width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))\n",
    "height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))\n",
    "fps    = int(cap.get(cv2.CAP_PROP_FPS))\n",
    "\n",
    "# 결과 저장용 VideoWriter\n",
    "fourcc = cv2.VideoWriter_fourcc(*\"mp4v\")\n",
    "output_video = cv2.VideoWriter(output_path, fourcc, fps, (width, height))\n",
    "\n",
    "print(\"▶ Processing... please wait\")\n",
    "\n",
    "while True:\n",
    "    ret, frame = cap.read()\n",
    "    if not ret:\n",
    "        break\n",
    "\n",
    "    # YOLO inference (이미지 → 객체 탐지 → 시각화)\n",
    "    results = model(frame, conf=0.4)\n",
    "\n",
    "    # results[0].plot() = 바운딩박스 시각화된 frame\n",
    "    annotated_frame = results[0].plot()\n",
    "\n",
    "    # 비디오 저장\n",
    "    output_video.write(annotated_frame)\n",
    "\n",
    "# 종료\n",
    "cap.release()\n",
    "output_video.release()\n",
    "\n",
    "print(f\"🎉 Done! Saved to: {output_path}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4c0ddfc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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