Upload app.py

app.py

@@ -39,9 +39,11 @@ def read_yolo_boxes(file_path):
     with open(file_path, 'r') as f:
         for line in f:
             parts = line.strip().split()
-            class_name = COCO_CLASSES[int(parts[0])]
-            x, y, w, h = map(float, parts[1:5])
-            boxes.append((class_name, x, y, w, h))
+            class_id = int(parts[0])
+            if COCO_CLASSES[class_id] != 'traffic light':  # Skip traffic lights
+                class_name = COCO_CLASSES[class_id]
+                x, y, w, h = map(float, parts[1:5])
+                boxes.append((class_name, x, y, w, h))
     return boxes
 
 def yolo_to_pixel_coord(x, y, img_width, img_height):
@@ -334,7 +336,7 @@ with gr.Blocks(title="Two-Step Train Obstruction Detection") as iface:
     with gr.Tab("Step 2: Object Detection"):
         object_input = gr.Image(type="numpy", label="Upload image for object detection")
         video_input = gr.Video(label="Or upload video for object detection")
-        frame_skip = gr.Slider(minimum=1, maximum=30, step=1, value=15, label="Frame Skip Rate (for video)")
+        frame_skip = gr.Slider(minimum=1, maximum=100, step=1, value=15, label="Frame Skip Rate (for video)")
         object_output = gr.Plot(label="Object Detection Result (Image)")
         video_output = gr.Video(label="Object Detection Result (Video)")
         object_message = gr.Textbox(label="Object Detection Results")