Update app.py

app.py

@@ -28,7 +28,7 @@ def enhance_image(image):
     kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
     sharpened = cv2.filter2D(image, -1, kernel)
     
-    # Apply adaptive thresholding for digital meter reading
+    # Adaptive thresholding
     thresholded = cv2.adaptiveThreshold(sharpened, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                         cv2.THRESH_BINARY, 11, 2)
     
@@ -40,7 +40,7 @@ def convert_to_rgb(image):
         image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
     return image
 
-# Detect Digital Meter Using YOLOv5 (Improved Confidence Threshold)
+# Detect Digital Meter Using YOLOv5
 def detect_meter(image):
     results = yolo_model(image)
     detected_meters = []
@@ -58,7 +58,7 @@ def extract_text_easyocr(image):
     text = " ".join(ocr_reader.readtext(image, detail=0))
     return text
 
-# Extract Text Using TrOCR (Fixed)
+# Extract Text Using TrOCR
 def extract_text_trocr(image):
     image = convert_to_rgb(image)  # Convert grayscale to RGB
     image = Image.fromarray(image)
@@ -70,17 +70,17 @@ def extract_text_trocr(image):
 # Extract Weight Using Regex
 def extract_weight(text):
     matches = re.findall(r'\d+\.\d+|\d+', text)  # Extract numeric weight
-    return matches[0] if matches else "Weight not detected"
+    return matches[0] if matches else None  # Returns None if no weight detected
 
-# Apply Statistical Filtering (Median Filtering for Stable Readings)
+# Apply Statistical Filtering for Stability
 def filter_weight_values(weights):
     if len(weights) > 1:
         weights = [float(w) for w in weights]
         filtered_weight = medfilt(weights, kernel_size=3)[-1]  # Smooth out variations
         return str(round(filtered_weight, 2))
-    return weights[0] if weights else "Weight not detected"
+    return weights[0] if weights else None
 
-# Full Processing Pipeline (With OCR Fallback)
+# Full Processing Pipeline (Dynamic Feedback)
 def process_image(image):
     enhanced = enhance_image(image)
     detected_meters = detect_meter(image)
@@ -93,12 +93,12 @@ def process_image(image):
     weight_easyocr = extract_weight(text_easyocr)
     weight_trocr = extract_weight(text_trocr)
 
-    final_weights = [weight_easyocr, weight_trocr]
-    final_weight = filter_weight_values([w for w in final_weights if w != "Weight not detected"])
-    
-    # Handle failed detection cases
-    if final_weight == "Weight not detected":
-        return "Try adjusting image clarity or detection thresholds"
+    final_weights = [w for w in [weight_easyocr, weight_trocr] if w]
+    final_weight = filter_weight_values(final_weights)
+
+    # Handle failed detection cases dynamically
+    if not final_weight:
+        return "Try adjusting image clarity or detection thresholds."
 
     return final_weight