Added Yolov5

run.py

@@ -1,16 +1,18 @@
 
 import gradio as gr
+import numpy as np
+import torch
+model = torch.hub.load('ultralytics/yolov5', 'custom', path='last2.pt', force_reload=True)
 
-
-def snap(image, video):
-    return [image, video]
-
+def detect(im):
+    results = model(im)
+    return [np.squeeze(results.render())]
+    #return [im]
 
 demo = gr.Interface(
-    snap,
-    [gr.Image(source="webcam", tool=None), gr.Video(source="webcam")],
-    ["image", "video"],
+    detect,
+    [gr.Image(source="webcam", tool=None)],
+    ["image"],
 )
-
 if __name__ == "__main__":
     demo.launch()