#!/usr/bin/env bash # kr_lp_pgnet 전용 컨테이너 안에서 실행되는 환경 셋업 스크립트. # # 컨테이너 가정: # - Ubuntu 24.04 + Python 3.10 + paddlepaddle-gpu sm_120 wheel 설치됨 # - 호스트 /home/cuuva/workspace ↔ 컨테이너 /workspace bind mount # - 이 repo는 /workspace/kr_lp_pgnet/, paddle wheel은 /workspace/wheels/ # # 실행 (호스트): # docker exec kr_lp_pgnet bash /workspace/kr_lp_pgnet/scripts/setup_server.sh set -euo pipefail SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" KR_LP_DIR="$(cd "$SCRIPT_DIR/.." && pwd)" WORKSPACE="${WORKSPACE:-$(cd "$KR_LP_DIR/.." && pwd)}" PADDLEOCR_DIR="$WORKSPACE/PaddleOCR" PRETRAIN_DIR="$PADDLEOCR_DIR/pretrain_models" WHEEL_DIR="$WORKSPACE/wheels" PY=python3.10 PIP="$PY -m pip" PIP_OPTS="--quiet --root-user-action=ignore" echo "[1/8] python3.10 + pip (deadsnakes PPA)" if ! command -v $PY >/dev/null 2>&1; then export DEBIAN_FRONTEND=noninteractive apt-get update -qq apt-get install -y -q software-properties-common ca-certificates curl add-apt-repository -y ppa:deadsnakes/ppa apt-get update -qq apt-get install -y -q python3.10 python3.10-venv python3.10-dev libgomp1 curl -sS https://bootstrap.pypa.io/get-pip.py | $PY fi $PY --version echo "[2/8] paddle 확인" if ! $PY -c 'import paddle; assert paddle.is_compiled_with_cuda()' 2>/dev/null; then echo " paddle 미설치 또는 CUDA 비호환. sm_120 wheel 설치..." WHL=$(ls "$WHEEL_DIR"/paddlepaddle_gpu-*-cp310-*linux_x86_64.whl 2>/dev/null | head -1) if [ -z "$WHL" ]; then echo " ERROR: $WHEEL_DIR/paddlepaddle_gpu-*-cp310-*.whl 없음" >&2 exit 1 fi $PIP install $PIP_OPTS "$WHL" fi $PY -c 'import paddle; print(" paddle:", paddle.__version__, "cuda:", paddle.is_compiled_with_cuda())' echo "[3/8] OpenCV 시스템 의존성 (libgl 등)" export DEBIAN_FRONTEND=noninteractive apt-get install -y -q libgl1 libglib2.0-0 libsm6 libxext6 libxrender1 wget git echo "[4/8] PaddleOCR clone (release/2.7)" if [ ! -d "$PADDLEOCR_DIR" ]; then git clone --depth 1 -b release/2.7 https://github.com/PaddlePaddle/PaddleOCR.git "$PADDLEOCR_DIR" fi cd "$PADDLEOCR_DIR" echo " PaddleOCR @$(git rev-parse --short HEAD)" echo "[5/8] PaddleOCR Python 의존성 (한 줄씩, 충돌 패키지는 skip)" # paddle은 이미 wheel로, blinker는 system pkg, opencv는 numpy2 비호환 → 제외 후 별도 설치 grep -viE '^(paddlepaddle|paddleocr|blinker|opencv-)' requirements.txt > /tmp/kr_lp_req.txt || true while IFS= read -r line; do [[ -z "$line" || "$line" =~ ^# ]] && continue $PIP install $PIP_OPTS --ignore-installed "$line" 2>/dev/null || echo " skip: $line" done < /tmp/kr_lp_req.txt echo "[6/8] OpenCV (numpy2 호환) + numpy<2 (PaddleOCR release/2.7 호환성) + wandb + cuDNN 9.17" $PIP install $PIP_OPTS 'opencv-python>=4.10' 'opencv-contrib-python>=4.10' wandb # paddle sm_120 wheel은 cuDNN 9.17 빌드라 paddle deps의 9.13.0.50을 9.17로 upgrade 필요. # (안 하면 conv2d에서 cublasLtCreate 심볼 로드 실패 → process abort) $PIP install $PIP_OPTS --upgrade 'nvidia-cudnn-cu13>=9.17,<9.18' # imgaug 등이 numpy 1.x API(np.sctypes)에 의존하므로 numpy 1.x로 핀. # paddle 3.3.0.dev는 numpy 1.x도 호환. $PIP install $PIP_OPTS 'numpy<2' --force-reinstall echo "[7/8] PGNet step1 pretrain weight 다운로드 + import smoke test" mkdir -p "$PRETRAIN_DIR" cd "$PRETRAIN_DIR" if [ ! -d train_step1 ]; then wget -q https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/train_step1.tar tar xf train_step1.tar && rm train_step1.tar fi ls train_step1/ cd "$PADDLEOCR_DIR" $PY -c " import sys; sys.path.insert(0, '.') from ppocr.modeling.architectures import build_model from ppocr.postprocess.pg_postprocess import PGPostProcess from ppocr.losses.e2e_pg_loss import PGLoss from ppocr.modeling.heads.e2e_pg_head import PGHead from ppocr.data.imaug.pg_process import PGProcessTrain print(' PGNet modules import OK') " echo "[8/8] dict / config symlink → PaddleOCR 트리" ln -sf "$KR_LP_DIR/dict/kr_lp_dict.txt" "$PADDLEOCR_DIR/ppocr/utils/kr_lp_dict.txt" mkdir -p "$PADDLEOCR_DIR/configs/e2e" ln -sf "$KR_LP_DIR/configs/kr_lp_pgnet.yml" "$PADDLEOCR_DIR/configs/e2e/kr_lp_pgnet.yml" ls -l "$PADDLEOCR_DIR/ppocr/utils/kr_lp_dict.txt" "$PADDLEOCR_DIR/configs/e2e/kr_lp_pgnet.yml" echo echo "===========================" echo "셋업 완료. 다음 단계:" echo " bash $KR_LP_DIR/data_gen/setup_assets.sh # 합성 자산 다운로드" echo " python3.10 $KR_LP_DIR/data_gen/generate_synthetic.py ... # 합성 데이터 생성" echo "==========================="