mirror of
https://github.com/RapidAI/RapidOCR.git
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locviettriandClaude Opus 4.6
1f78b76eb4
Replace the single legacy Dockerfile (rapidocr_api only) with 7 per-engine development images covering all supported inference backends: - onnxruntime-cpu: ONNX Runtime on CPU (python:3.10-slim-bookworm) - onnxruntime-gpu: ONNX Runtime with CUDA (nvidia/cuda:12.4.1) - tensorrt: NVIDIA TensorRT (nvcr.io/nvidia/deepstream:7.0-gc-triton-devel) - paddle: PaddlePaddle CPU - openvino: Intel OpenVINO - pytorch: PyTorch CPU - mnn: Alibaba MNN Infrastructure: - Dockerfile.base: shared foundation for CPU variants - docker-compose.yaml: all 7 services with shared model volume - Makefile: make build-*/test-*/shell-* convenience commands - .dockerignore: excludes .git, models, build artifacts Key design decisions: - PYTHONPATH-based imports (setup.py incompatible with pip editable install) - Named volume (rapidocr-models) for persistent model cache across rebuilds - Source bind-mounted at runtime for live editing - tensorrt pinned to 8.6.x + cuda-python 12.x (matching DeepStream 7.0) All 7 images built and tested with full OCR pipeline inference. Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
21 lines
322 B
Plaintext
21 lines
322 B
Plaintext
.git
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__pycache__
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*.pyc
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*.pyo
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*.egg-info
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dist/
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build/
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.tox/
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.pytest_cache/
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.mypy_cache/
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python/rapidocr/models/
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python/benchmark_*
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python/pred.txt
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python/merged_benchmark_report_*
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python/tensorrt_build_logs_*
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python/validate_benchmark_*
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python/generate_merged_report.py
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python/mnn_benchmark_reference.md
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*.engine
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.mcp.json
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