Update app.py

app.py

@@ -37,51 +37,6 @@ def image_fn(
   
   
         
-def video_fn(model_path, video_file, conf_thres, iou_thres, start_sec, duration):
-    model = yolov7.load(model_path, device="cpu", hf_model=True, trace=False)
-    start_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec))
-    end_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec + duration))
-
-    suffix = Path(video_file).suffix
-
-    clip_temp_file = tempfile.NamedTemporaryFile(suffix=suffix)
-    subprocess.call(
-        f"ffmpeg -y -ss {start_timestamp} -i {video_file} -to {end_timestamp} -c copy {clip_temp_file.name}".split()
-    )
-
-    # Reader of clip file
-    cap = cv2.VideoCapture(clip_temp_file.name)
-
-    # This is an intermediary temp file where we'll write the video to
-    # Unfortunately, gradio doesn't play too nice with videos rn so we have to do some hackiness
-    # with ffmpeg at the end of the function here.
-    with tempfile.NamedTemporaryFile(suffix=".mp4") as temp_file:
-        out = cv2.VideoWriter(temp_file.name, cv2.VideoWriter_fourcc(*"MP4V"), 30, (1280, 720))
-
-        num_frames = 0
-        max_frames = duration * 30
-        while cap.isOpened():
-            try:
-                ret, frame = cap.read()
-                if not ret:
-                    break
-            except Exception as e:
-                print(e)
-                continue
-            print("FRAME DTYPE", type(frame))
-            out.write(model([frame], conf_thres, iou_thres))
-            num_frames += 1
-            print("Processed {} frames".format(num_frames))
-            if num_frames == max_frames:
-                break
-
-        out.release()
-
-        # Aforementioned hackiness
-        out_file = tempfile.NamedTemporaryFile(suffix="out.mp4", delete=False)
-        subprocess.run(f"ffmpeg -y -loglevel quiet -stats -i {temp_file.name} -c:v libx264 {out_file.name}".split())
-
-    return out_file.name
 
 image_interface = gr.Interface(
     fn=image_fn,
@@ -106,31 +61,9 @@ image_interface = gr.Interface(
 )
 
 
-video_interface = gr.Interface(
-    fn=video_fn,
-    inputs=[
-        gr.inputs.Video(source = "upload", type = "mp4", label = "Input Video"),
-        gr.inputs.Dropdown(
-        choices=[
-            "Aalaa/Yolov7_Visual_Pollution_Detection",
-        ],
-        default="Aalaa/Yolov7_Visual_Pollution_Detection",
-        label="Model",
-    ),
-    ],
-    outputs=gr.outputs.Video(type = "mp4", label = "Output Video"),
-    # examples=[
-    #     ["video.mp4", 0.25, 0.45, 0, 2],
-       
-    # ],
-    title="Smart Environmental Eye (SEE)",
-    cache_examples=True,
-    theme='huggingface',
-   
-)
 
 if __name__ == "__main__":
     gr.TabbedInterface(
-        [image_interface, video_interface],
-        ["Run on Images", "Run on Videos"],
+        [image_interface],
+        ["Run on Images"],
     ).launch()