Update app.py

app.py

@@ -9,14 +9,12 @@ from typing import Optional
 from pydantic import BaseModel
 from rapidocr_onnxruntime import RapidOCR
 
-# Khởi tạo FastAPI và OCR engine
 app = FastAPI(title="OCR API", description="RapidOCR API Service")
 engine = RapidOCR()
 
 def process_ocr(image: np.ndarray, use_det: bool, use_cls: bool, use_rec: bool) -> list:
     """Xử lý OCR và trả về kết quả"""
     img_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
-    print(use_det, use_cls, use_rec)
     result, _ = engine(img_bgr, use_det=use_det, use_cls=use_cls, use_rec=use_rec)
     
     if not result:
@@ -41,22 +39,6 @@ def process_ocr(image: np.ndarray, use_det: bool, use_cls: bool, use_rec: bool)
     
     return texts
 
-@app.get("/")
-async def root():
-    """Root endpoint - hướng dẫn sử dụng API"""
-    return {
-        "message": "OCR API is running",
-        "endpoints": {
-            "POST /ocr": "Upload image file for OCR",
-            "POST /ocr/url": "Provide image URL for OCR",
-            "GET /health": "Health check"
-        },
-        "usage": {
-            "curl_example": 'curl -X POST https://your-space.hf.space/ocr -F "file=@image.jpg"',
-            "python_example": "requests.post('https://your-space.hf.space/ocr', files={'file': open('image.jpg', 'rb')})"
-        }
-    }
-
 @app.post("/ocr")
 async def ocr_from_file(
     file: UploadFile = File(..., description="Image file to process"),
@@ -64,14 +46,10 @@ async def ocr_from_file(
     use_cls: bool = Form(True, description="Use classification"),
     use_rec: bool = Form(True, description="Use recognition")
 ):
-    """OCR from uploaded image file"""
-    
-    # Validate file type
     if not file.content_type or not file.content_type.startswith('image/'):
         raise HTTPException(status_code=400, detail="File must be an image")
     
     try:
-        # Read and process image
         contents = await file.read()
         image = Image.open(io.BytesIO(contents))
         
@@ -91,52 +69,11 @@ async def ocr_from_file(
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
 
-class OCRUrlRequest(BaseModel):
-    url: str
-    use_det: Optional[bool] = True
-    use_cls: Optional[bool] = True
-    use_rec: Optional[bool] = True
-
-@app.post("/ocr/url")
-async def ocr_from_url(request: OCRUrlRequest):
-    """OCR from image URL"""
-    
-    try:
-        # Download image from URL
-        response = requests.get(request.url, timeout=30)
-        response.raise_for_status()
-        
-        image = Image.open(io.BytesIO(response.content))
-        
-        if image.mode != 'RGB':
-            image = image.convert('RGB')
-        
-        img_np = np.array(image)
-        results = process_ocr(
-            img_np, 
-            request.use_det, 
-            request.use_cls, 
-            request.use_rec
-        )
-        
-        return JSONResponse(content={
-            "success": True,
-            "texts": [item["text"] for item in results],
-            "details": results,
-            "num_texts": len(results)
-        })
-    
-    except requests.RequestException as e:
-        raise HTTPException(status_code=400, detail=f"Failed to fetch image: {str(e)}")
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
-
 @app.get("/health")
 async def health_check():
     """Health check endpoint"""
-    return {"status": "healthy", "service": "RapidOCR API"}
+    return {"status": "healthy", "service": "XOCR AI"}
 
-# Chạy với uvicorn (Hugging Face sẽ tự gọi cái này)
 if __name__ == "__main__":
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=7860)