Update app.py

app.py

@@ -38,25 +38,23 @@ def load_models():
 # Load models
 full_plate_model, character_model, recognition_model = load_models()
 
-# Function to detect and crop license plates
-def detect_and_crop_license_plate(image):
+# Function to detect license plates and prepare for character recognition
+def process_license_plate(image):
     img_bgr = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
     results = full_plate_model(img_bgr)
 
     detected_image = img_bgr.copy()
-    cropped_images = []
     for result in results:
         if hasattr(result, 'boxes') and result.boxes is not None:
             for box in result.boxes.xyxy:
                 x1, y1, x2, y2 = map(int, box)
                 cv2.rectangle(detected_image, (x1, y1), (x2, y2), (255, 0, 0), 2)  # Draw bounding box
-                cropped_image = img_bgr[y1:y2, x1:x2]
-                cropped_images.append(cropped_image)
 
-    return cropped_images, detected_image
+    return detected_image, img_bgr
 
-# Function to detect and crop characters
-def detect_and_crop_characters(image):
+# Function to detect and recognize characters directly from the original image
+def detect_and_recognize_characters(image):
+    # Detect characters
     results = character_model(image)
     character_crops = []
     for result in results:
@@ -64,7 +62,14 @@ def detect_and_crop_characters(image):
             for box in result.boxes.xyxy:
                 x1, y1, x2, y2 = map(int, box)
                 character_crops.append(image[y1:y2, x1:x2])
-    return character_crops
+    
+    # Recognize characters
+    if character_crops:
+        recognized_characters = recognize_characters(character_crops)
+    else:
+        recognized_characters = []
+
+    return recognized_characters
 
 # Function to recognize characters
 def recognize_characters(character_crops):
@@ -93,31 +98,19 @@ if uploaded_file is not None:
     # Load image
     image = Image.open(uploaded_file)
 
-    # Detect license plates
+    # Process the image for license plate detection
     with st.spinner("Processing image..."):
-        cropped_plates, detected_image = detect_and_crop_license_plate(image)
+        detected_image, original_image = process_license_plate(image)
 
-        if cropped_plates:
-            st.image(cv2.cvtColor(detected_image, cv2.COLOR_BGR2RGB), caption="Detected License Plates", use_container_width=True)
-            st.write(f"Detected {len(cropped_plates)} license plate(s).")
+        # Show the detected image with bounding boxes
+        st.image(cv2.cvtColor(detected_image, cv2.COLOR_BGR2RGB), caption="Detected License Plates", use_container_width=True)
 
-            for idx, cropped_plate in enumerate(cropped_plates, 1):
-                st.write(f"Processing License Plate {idx}:")
-                character_crops = detect_and_crop_characters(cropped_plate)
+        # Perform character detection and recognition on the original image
+        recognized_characters = detect_and_recognize_characters(original_image)
 
-                if character_crops:
-                    recognized_characters = recognize_characters(character_crops)
-                    st.write("Recognized Characters:", "".join(recognized_characters))
-                else:
-                    st.write("No characters detected in this license plate.")
+        if recognized_characters:
+            st.write("Recognized Characters:", "".join(recognized_characters))
         else:
-            st.write("No license plates detected. Running character detection on the full image.")
-            character_crops = detect_and_crop_characters(cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR))
-
-            if character_crops:
-                recognized_characters = recognize_characters(character_crops)
-                st.write("Recognized Characters:", "".join(recognized_characters))
-            else:
-                st.write("No characters detected in the full image.")
+            st.write("No characters detected in the image.")
 
     st.success("Processing complete!")