Update app.py

app.py

@@ -20,7 +20,7 @@ ocr_reader = easyocr.Reader(["en"])  # EasyOCR
 trocr_processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-stage1")
 trocr_model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-stage1").to(device)
 
-# Image Preprocessing (Sharpen & Adaptive Threshold)
+# Image Preprocessing (Adaptive Threshold & Sharpening)
 def enhance_image(image):
     image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     
@@ -40,7 +40,7 @@ def convert_to_rgb(image):
         image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
     return image
 
-# Detect Digital Meter Using YOLOv5
+# Detect Digital Meter Using YOLOv5 (Improved Confidence Threshold)
 def detect_meter(image):
     results = yolo_model(image)
     detected_meters = []
@@ -48,7 +48,7 @@ def detect_meter(image):
     for result in results:
         if hasattr(result, "boxes"):  # Ensure correct format
             for box in result.boxes:
-                if box.conf > 0.3:  # Lower confidence threshold for better detection
+                if box.conf > 0.25:  # Lower confidence threshold for better detection
                     detected_meters.append(box.xyxy.tolist())
 
     return detected_meters
@@ -80,10 +80,12 @@ def filter_weight_values(weights):
         return str(round(filtered_weight, 2))
     return weights[0] if weights else "Weight not detected"
 
-# Full Processing Pipeline
+# Full Processing Pipeline (With OCR Fallback)
 def process_image(image):
     enhanced = enhance_image(image)
     detected_meters = detect_meter(image)
+
+    # OCR Extraction
     text_easyocr = extract_text_easyocr(enhanced)
     text_trocr = extract_text_trocr(enhanced)
 
@@ -94,7 +96,11 @@ def process_image(image):
     final_weights = [weight_easyocr, weight_trocr]
     final_weight = filter_weight_values([w for w in final_weights if w != "Weight not detected"])
     
-    return final_weight or "Weight not detected"
+    # Handle failed detection cases
+    if final_weight == "Weight not detected":
+        return "Try adjusting image clarity or detection thresholds"
+
+    return final_weight
 
 # Gradio Interface
 iface = gr.Interface(fn=process_image, inputs="image", outputs="text")