mirror of
https://github.com/snapotter-hq/SnapOtter.git
synced 2026-08-03 07:46:42 +02:00
Siddharth Kumar Sah
29a382e9e0
Add a :cuda Docker image tag that auto-detects NVIDIA GPU at runtime and falls back gracefully to CPU. Same pattern as Immich. - New gpu.py shared utility for cached CUDA detection - Background removal (rembg): pass CUDAExecutionProvider to ONNX Runtime - Upscaling (Real-ESRGAN): use CUDA device + FP16 when GPU available - OCR (PaddleOCR): enable use_gpu when CUDA detected - Dispatcher reports GPU status at startup via readiness signal - Admin health endpoint exposes GPU availability - Dockerfile uses ARG GPU=false with conditional NVIDIA CUDA base image - docker-compose.gpu.yml override for GPU users - CI/CD workflows build and publish :cuda tag (amd64 only) Three tags: :latest (CPU), :lite (no AI), :cuda (GPU with CPU fallback)
113 lines
3.4 KiB
Python
113 lines
3.4 KiB
Python
"""Text extraction from images using Tesseract or PaddleOCR."""
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import sys
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import json
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import os
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def emit_progress(percent, stage):
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"""Emit structured progress to stderr for bridge.ts to capture."""
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print(json.dumps({"progress": percent, "stage": stage}), file=sys.stderr, flush=True)
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def run_tesseract(input_path, language):
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"""Run Tesseract OCR."""
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import subprocess
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lang_map = {"en": "eng", "de": "deu", "fr": "fra", "es": "spa", "zh": "chi_sim", "ja": "jpn", "ko": "kor"}
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tess_lang = lang_map.get(language, "eng")
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emit_progress(30, "Scanning")
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result = subprocess.run(
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["tesseract", input_path, "stdout", "-l", tess_lang],
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capture_output=True,
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text=True,
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timeout=120,
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)
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emit_progress(70, "Extracting text")
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text = result.stdout.strip()
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if result.returncode != 0 and not text:
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raise RuntimeError(result.stderr.strip() or "Tesseract failed")
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return text, "tesseract"
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def run_paddleocr(input_path, language):
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"""Run PaddleOCR."""
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os.environ["PADDLE_PDX_DISABLE_MODEL_SOURCE_CHECK"] = "True"
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from paddleocr import PaddleOCR
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from gpu import gpu_available
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emit_progress(20, "Loading")
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ocr = PaddleOCR(lang=language, use_gpu=gpu_available())
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emit_progress(30, "Scanning")
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result = ocr.ocr(input_path)
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emit_progress(70, "Extracting text")
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text = "\n".join(
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[
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line[1][0]
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for res in result
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if res
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for line in res
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if line and line[1]
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]
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)
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return text, "paddleocr"
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def main():
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input_path = sys.argv[1]
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settings = json.loads(sys.argv[2]) if len(sys.argv) > 2 else {}
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engine = settings.get("engine", "tesseract")
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language = settings.get("language", "en")
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try:
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emit_progress(10, "Preparing")
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if engine == "paddleocr":
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try:
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text, used_engine = run_paddleocr(input_path, language)
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except ImportError:
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print(
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json.dumps(
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{
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"success": False,
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"error": "PaddleOCR is not installed",
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}
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)
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)
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sys.exit(1)
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except Exception:
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# PaddleOCR failed at runtime — fall back to Tesseract
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emit_progress(25, "Falling back")
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try:
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text, used_engine = run_tesseract(input_path, language)
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except FileNotFoundError:
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print(
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json.dumps({"success": False, "error": "OCR engines unavailable"})
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)
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sys.exit(1)
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else:
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try:
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text, used_engine = run_tesseract(input_path, language)
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except FileNotFoundError:
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print(
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json.dumps(
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{
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"success": False,
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"error": "Tesseract is not installed",
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}
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)
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)
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sys.exit(1)
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emit_progress(95, "Done")
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print(json.dumps({"success": True, "text": text, "engine": used_engine}))
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except Exception as e:
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print(json.dumps({"success": False, "error": str(e)}))
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sys.exit(1)
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if __name__ == "__main__":
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main()
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