Update utils/image_processor.py

utils/image_processor.py

@@ -30,32 +30,21 @@ def preprocess_image(image):
 
 def extract_text_from_image(image_path):
     """
-    Extract text using TrOCR from a handwritten image
+    Extract handwritten text from an image using TrOCR
     """
     try:
-        if not trocr_available:
-            raise ValueError("TrOCR is not available.")
+        print(f"📂 Reading image from: {image_path}")  # ✅ log file path
 
-        print(f"📂 Reading image from: {image_path}")
+        image = Image.open(image_path).convert("RGB")
+        pixel_values = processor(images=image, return_tensors="pt").pixel_values
 
-        # Read and preprocess image
-        image = cv2.imread(image_path)
-        if image is None:
-            raise ValueError(f"Could not load image: {image_path}")
+        generated_ids = trocr_model.generate(pixel_values)
+        text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
 
-        processed_image = preprocess_image(image)
-        pil_image = Image.fromarray(processed_image).convert("RGB")
-
-        # TrOCR expects pixel values between 0-1
-        pixel_values = processor(images=pil_image, return_tensors="pt").pixel_values
-
-        # Disable gradient for inference
-        with torch.no_grad():
-            generated_ids = model.generate(pixel_values)
-            generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-
-        return generated_text.strip() or "Text extraction failed. Please enter text manually."
+        print(f"📝 Extracted Text from {os.path.basename(image_path)}: {text}")  # ✅ PRINT EXTRACTED TEXT
 
+        return text or "Text extraction failed."
+    
     except Exception as e:
-        print(f"OCR failed: {e}")
-        return "Text extraction failed. Please enter text manually."
+        print(f"❌ OCR failed on {image_path}: {str(e)}")
+        return "Text extraction failed."