Update app.py

app.py

@@ -21,7 +21,7 @@ model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', source="l
 
 def yolo(im, size=1024):
     g = (size / max(im.size))  # gain
-    im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS)  # resize
+    im = im.resize((int(x * g) for x in im.size), Image.BICUBIC)  # resize
 
     results = model(im)  # inference
     results.render()  # updates results.imgs with boxes and labels