| from fastapi import FastAPI, UploadFile, File, HTTPException |
| from fastapi.responses import JSONResponse |
| import numpy as np |
| from PIL import Image |
| import io |
| import uvicorn |
| import os |
|
|
| |
| os.environ['EASYOCR_MODULE_PATH'] = '/app/model' |
| os.environ['HOME'] = '/app' |
|
|
| import easyocr |
|
|
| app = FastAPI() |
|
|
| |
| reader = easyocr.Reader(['es', 'en']) |
|
|
| @app.post("/ocr") |
| async def extract_text(file: UploadFile = File(...)): |
| """ |
| Extrae texto de una imagen usando OCR |
| """ |
| try: |
| |
| if not file.content_type.startswith('image/'): |
| raise HTTPException(status_code=400, detail="El archivo debe ser una imagen") |
| |
| |
| contents = await file.read() |
| |
| |
| image = Image.open(io.BytesIO(contents)) |
| |
| |
| if image.mode != 'RGB': |
| image = image.convert('RGB') |
| |
| |
| image_array = np.array(image) |
| |
| |
| results = reader.readtext(image_array) |
| |
| |
| extracted_text = [] |
| for (bbox, text, confidence) in results: |
| extracted_text.append({ |
| "text": text, |
| "confidence": float(confidence), |
| "bbox": bbox |
| }) |
| |
| |
| full_text = " ".join([item["text"] for item in extracted_text]) |
| |
| return JSONResponse(content={ |
| "success": True, |
| "full_text": full_text, |
| "detailed_results": extracted_text |
| }) |
| |
| except Exception as e: |
| raise HTTPException(status_code=500, detail=f"Error procesando la imagen: {str(e)}") |
|
|
| @app.get("/") |
| async def root(): |
| return {"message": "OCR API funcionando", "endpoint": "/ocr"} |
|
|
| if __name__ == "__main__": |
| port = int(os.environ.get("PORT", 7860)) |
| uvicorn.run(app, host="0.0.0.0", port=port) |
|
|
