Update app.py

app.py

@@ -5,11 +5,9 @@ import os
 import easyocr
 from moviepy import ImageSequenceClip
 
-
 st.title("🚗 PlateVision 🔍")
 st.caption("AI-powered license plate detection & recognition from images and videos")
 
-
 os.makedirs("input", exist_ok=True)
 os.makedirs("output", exist_ok=True)
 
@@ -24,47 +22,36 @@ def load_ocr_reader():
 def process_and_find_plate(input_path, output_path):
     extension = os.path.splitext(input_path)[1].lower()
     if extension in ['.mp4', '.mkv']:
-        path = find_plate_on_video(input_path, output_path)
-
+        return find_plate_on_video(input_path, output_path)
     elif extension in ['.jpg', '.jpeg', '.png']:
-        path = find_plate_on_image(input_path, output_path)
-     
+        return find_plate_on_image(input_path, output_path)
     else:
         st.error("Unsupported file type")
         return None
 
-    return path
-    
 def find_plate_on_image(input_path, output_path):
-    
     model = load_yolo_model()
     reader = load_ocr_reader()
-    
+
     image = cv2.imread(input_path)
     image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
     outputs = model.predict(image, verbose=False)
-    
+
     for output in outputs:
         for box in output.boxes:
             x1, y1, x2, y2 = map(int, box.xyxy[0])
             confidence = box.conf[0]
             roi = image[y1:y2, x1:x2]
             results = reader.readtext(roi)
-            try:
-                plate_num = results[0][1].strip()
-            except Exception as e:
-               plate_num = "" 
-                
-            if plate_num == "":
-                plate_num = "Not Visible!" 
-                
+            plate_num = results[0][1].strip() if results else "Not Visible!"
             cv2.rectangle(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
-            cv2.putText(image, f'{confidence*100:.2f}%', (x1, y1-20), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2, cv2.LINE_AA)
-            cv2.putText(image, f'Number: {plate_num}', (x1, y2+20), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2, cv2.LINE_AA)            
-              
-    cv2.imwrite(output_path, image)
+            cv2.putText(image, f'{confidence*100:.2f}%', (x1, y1 - 20),
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+            cv2.putText(image, f'Number: {plate_num}', (x1, y2 + 20),
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+
+    cv2.imwrite(output_path, cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
     return output_path
-            
 
 def find_plate_on_video(input_path, output_path):
     model = load_yolo_model()
@@ -75,11 +62,11 @@ def find_plate_on_video(input_path, output_path):
         st.error("Error opening the video")
         return None
 
-    fps = int(cap.get(cv2.CAP_PROP_FPS))
-    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-    frames = [] 
+    fps = int(cap.get(cv2.CAP_PROP_FPS)) or 25
+    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) or 1
+    frames = []
     frame_idx = 0
-    skip_frame = 5
+    skip_frame = 5  # ✅ define properly
 
     progress_bar = st.progress(0, text="🔍 Analyzing video frames...")
 
@@ -88,49 +75,39 @@ def find_plate_on_video(input_path, output_path):
         if not ret:
             break
 
-        if frame_idx % skip_frame != 0:
-            continue
-
-        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-        outputs = model.predict(rgb_frame, verbose=False)
-
-        for output in outputs:
-            for box in output.boxes:
-                x1, y1, x2, y2 = map(int, box.xyxy[0])
-                confidence = box.conf[0]
-                roi = frame[y1:y2, x1:x2]
-                results = reader.readtext(roi)
-                try:
-                    plate_num = results[0][1].strip()
-                except Exception:
-                    plate_num = ""
-
-                if plate_num == "":
-                    plate_num = "Not Visible!"
-                cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
-                cv2.putText(frame, f'{confidence*100:.2f}%', (x1, y1 - 20),
-                            cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
-                cv2.putText(frame, f'Number: {plate_num}', (x1, y2 + 20),
-                            cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
-
-        frames.append(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
-        frame_idx += 1
+        if frame_idx % skip_frame == 0:
+            rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            outputs = model.predict(rgb_frame, verbose=False)
+
+            for output in outputs:
+                for box in output.boxes:
+                    x1, y1, x2, y2 = map(int, box.xyxy[0])
+                    confidence = box.conf[0]
+                    roi = frame[y1:y2, x1:x2]
+                    results = reader.readtext(roi)
+                    plate_num = results[0][1].strip() if results else "Not Visible!"
+                    cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
+                    cv2.putText(frame, f'{confidence*100:.2f}%', (x1, y1 - 20),
+                                cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
+                    cv2.putText(frame, f'Number: {plate_num}', (x1, y2 + 20),
+                                cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
+
+            frames.append(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
 
-        # Update progress
+        frame_idx += 1
         progress = min(frame_idx / total_frames, 1.0)
         progress_bar.progress(progress, text=f"📸 Processed {frame_idx}/{total_frames} frames...")
 
     cap.release()
     progress_bar.empty()
 
-    # Write final video using MoviePy
-    clip = ImageSequenceClip(frames, fps=fps // frame_skip if fps >= frame_skip else 1)
+    # ✅ fix undefined variable (use skip_frame)
+    output_fps = max(fps // skip_frame, 1)
+    clip = ImageSequenceClip(frames, fps=output_fps)
     clip.write_videofile(output_path, codec='libx264', audio=False, logger=None)
 
     return output_path
 
-        
-
 uploaded_file = st.file_uploader("📤 Upload an image or video", type=['jpg', 'jpeg', 'png', 'mp4', 'mkv'])
 
 if uploaded_file is not None:
@@ -138,19 +115,14 @@ if uploaded_file is not None:
     output_path = f"output/{uploaded_file.name}"
     with open(input_path, 'wb') as f:
         f.write(uploaded_file.getbuffer())
+
     with st.spinner("🚦 Detecting plates... please fasten your seatbelt!"):
         path = process_and_find_plate(input_path, output_path)
 
-    if path.endswith(('.mp4', '.mkv')):
-        video_file = open(path, 'rb')
-        video_bytes = video_file.read()
-        st.video(video_bytes)
-    elif path.endswith(('.jpg', '.jpeg', '.png')):
+    if path and path.endswith(('.mp4', '.mkv')):
+        with open(path, 'rb') as video_file:
+            st.video(video_file.read())
+    elif path and path.endswith(('.jpg', '.jpeg', '.png')):
         st.image(path)
     else:
-        st.error("Error occured while proccessing the file.")
-    
-
-
-    
-
+        st.error("Error occurred while processing the file.")