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| import os | |
| import io | |
| import easyocr | |
| from fastapi import FastAPI, UploadFile, File | |
| from fastapi.responses import JSONResponse | |
| from PIL import Image | |
| # ========================= | |
| # EasyOCR config | |
| # ========================= | |
| MODEL_DIR = "/app/.EasyOCR" | |
| USER_NET_DIR = os.path.join(MODEL_DIR, "user_network") | |
| os.makedirs(MODEL_DIR, exist_ok=True) | |
| os.makedirs(USER_NET_DIR, exist_ok=True) | |
| # β preload reader with cached models | |
| reader = easyocr.Reader( | |
| ['en', 'hi'], # langs (can reduce to ['en'] if you want smaller image) | |
| model_storage_directory=MODEL_DIR, | |
| user_network_directory=USER_NET_DIR, | |
| download_enabled=False # π« no runtime downloads | |
| ) | |
| # ========================= | |
| # FastAPI app | |
| # ========================= | |
| app = FastAPI() | |
| async def root(): | |
| return {"message": "OCR API is running on Hugging Face π"} | |
| async def ocr(file: UploadFile = File(...)): | |
| try: | |
| # read image into memory | |
| contents = await file.read() | |
| image = Image.open(io.BytesIO(contents)) | |
| # run OCR | |
| results = reader.readtext(image) | |
| # format results | |
| text_results = [] | |
| for bbox, text, prob in results: | |
| text_results.append({ | |
| "bbox": bbox, | |
| "text": text, | |
| "confidence": float(prob) | |
| }) | |
| return JSONResponse(content={"results": text_results}) | |
| except Exception as e: | |
| return JSONResponse(content={"error": str(e)}, status_code=500) | |