{ "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, 25,849,024 parameters, 0 gradients, 78.7 GFLOPs\n", "\n", "\u001b[34m\u001b[1mPyTorch:\u001b[0m starting from '/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_final2/weights/best_fashion_16class.pt' with input shape (1, 3, 640, 640) BCHW and output shape(s) (1, 20, 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 ✅ 0.8s, saved as '/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_final2/weights/best_fashion_16class.onnx' (98.9 MB)\n", "\n", "Export complete (1.1s)\n", "Results saved to \u001b[1m/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_final2/weights\u001b[0m\n", "Predict: yolo predict task=detect model=/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_final2/weights/best_fashion_16class.onnx imgsz=640 \n", "Validate: yolo val task=detect model=/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_final2/weights/best_fashion_16class.onnx imgsz=640 data=/home/cuuva/experiment/datasets/fashionpedia_yolo/fashionpedia_reduced.yaml \n", "Visualize: https://netron.app\n" ] }, { "data": { "text/plain": [ "'/home/cuuva/experiment/fashion_yolo/fashionpedia_exp/yolov8m_fashion_final2/weights/best_fashion_16class.onnx'" ] }, "execution_count": 1, "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": [] } ], "metadata": { "kernelspec": { "display_name": "1stagedetect", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.18" } }, "nbformat": 4, "nbformat_minor": 5 }