update

app.py

@@ -37,24 +37,6 @@ def yolov7_inference(
     results = model([image], size=image_size)
     return results.render()[0]
         
-def yolov7_inference_video(
-    video: gr.inputs.Video = None,
-    model_path: gr.inputs.Dropdown = None,
-    
-):
-    """
-    YOLOv7 inference function
-    Args:
-        video: Input video
-        model_path: Path to the model
-    
-    Returns:
-        Rendered video
-    """
-
-    model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
-    results = model([video])
-    return results
 
 
 inputs = [
@@ -74,7 +56,7 @@ inputs = [
     #gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold")
 ]
 
-outputs = [gr.outputs.Image(type="filepath", label="Output Image"), gr.outputs.Video(type="filepath", label="Output Video")]
+outputs = gr.outputs.Image(type="filepath", label="Output Image")
 title = "Smart Environmental Eye (SEE)"
 
 examples = [['image1.jpg', 'alshimaa/model_yolo7', 640, 0.25, 0.45], ['image2.jpg', 'alshimaa/model_yolo7', 640, 0.25, 0.45], ['image3.jpg', 'alshimaa/model_yolo7', 640, 0.25, 0.45]]
@@ -87,14 +69,6 @@ demo_app = gr.Interface(
     cache_examples=True,
     theme='huggingface',
 )
-demo_app_video = gr.Interface(
-    fn=yolov7_inference_video,
-    inputs=inputs,
-    outputs=outputs,
-    title=title,
-    examples=examples,
-    cache_examples=True,
-    theme='huggingface',
-)
+
 demo_app.launch(debug=True, enable_queue=True)
-demo_app_video.launch(debug=True, enable_queue=True)
+