69 lines
2.1 KiB
Docker
69 lines
2.1 KiB
Docker
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# Dockerfile.gpu - CUDA-enabled PaddleOCR REST API
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# Supports: x86_64 with NVIDIA GPU (CUDA 12.x)
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# For DGX Spark (ARM64 + CUDA): build natively on the device
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FROM nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04
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LABEL maintainer="Sergio Jimenez"
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LABEL description="PaddleOCR Tuning REST API - GPU/CUDA version"
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WORKDIR /app
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# Set environment variables
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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ENV CUDA_VISIBLE_DEVICES=0
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# Install Python 3.11 and system dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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python3.11 \
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python3.11-venv \
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python3-pip \
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libgl1 \
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libglib2.0-0 \
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libsm6 \
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libxext6 \
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libxrender1 \
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libgomp1 \
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&& rm -rf /var/lib/apt/lists/* \
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&& ln -sf /usr/bin/python3.11 /usr/bin/python
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# Install Python dependencies from requirements file
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COPY requirements-gpu.txt .
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RUN pip install --no-cache-dir -r requirements-gpu.txt
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# Copy application code
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COPY paddle_ocr_tuning_rest.py .
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COPY dataset_manager.py .
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# Build arguments for models to bake into image
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ARG DET_MODEL=PP-OCRv5_server_det
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ARG REC_MODEL=PP-OCRv5_server_rec
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# Set as environment variables (can be overridden at runtime)
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ENV PADDLE_DET_MODEL=${DET_MODEL}
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ENV PADDLE_REC_MODEL=${REC_MODEL}
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# Download models during build (not at runtime)
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RUN python -c "\
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import os; \
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from paddleocr import PaddleOCR; \
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det = os.environ.get('PADDLE_DET_MODEL', 'PP-OCRv5_server_det'); \
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rec = os.environ.get('PADDLE_REC_MODEL', 'PP-OCRv5_server_rec'); \
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print(f'Downloading models: det={det}, rec={rec}'); \
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ocr = PaddleOCR(text_detection_model_name=det, text_recognition_model_name=rec); \
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print('Models downloaded successfully!')"
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# Volume for dataset and optional additional model cache
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VOLUME ["/app/dataset", "/root/.paddlex"]
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# Expose API port
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EXPOSE 8000
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')" || exit 1
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# Run the API server
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CMD ["uvicorn", "paddle_ocr_tuning_rest:app", "--host", "0.0.0.0", "--port", "8000"]
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