kr_lp_pgnet/scripts/setup_server.sh

#!/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 "==========================="