Update app.py

app.py

@@ -10,19 +10,21 @@ from PIL import Image
 models = ["model_weights/md_v5a.0.0.pt","model_weights/md_v5b.0.0.pt"]
 model = torch.hub.load('ultralytics/yolov5', 'custom', "model_weights/md_v5a.0.0.pt")
 
-def yolo(im, model):
+def yolo(im, chosen_model, size):
     g = (size / max(im.size))  # gain
     im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS)  # resize
-
+    
+    model = torch.hub.load('ultralytics/yolov5', 'custom', "model_weights/md_v5a.0.0.pt")
+    
     results = model(im)  # inference
     results.render()  # updates results.imgs with boxes and labels
     return Image.fromarray(results.imgs[0])
 
 image = gr.inputs.Image(type="pil", label="Input Image")
-model = gr.inputs.Model(choices = models, value = "model_weights/md_v5a.0.0.pt",type = "value", label="Model Weight")
+chosen_model = gr.inputs.Dropdown(choices = models, value = "model_weights/md_v5a.0.0.pt",type = "value", label="Model Weight")
 size = 640
 
-inputs = [image, model, size]
+inputs = [image, chosen_model, size]
 
 outputs = gr.outputs.Image(type="pil", label="Output Image")