get model selection field

app.py

@@ -4,8 +4,9 @@ import torchvision
 import torch
 
 # load model
+MODELS_TYPE = ["ModelA", "ModelB", "ModelC"]
 
-def predict(input_image):
+def predict(input_image, model_name):
     pil_image = Image.fromarray(input_image.astype('uint8'), 'RGB')
     # transform image to torch and do preprocessing
     torch_image = torchvision.transforms.ToTensor()(pil_image)
@@ -18,10 +19,13 @@ def predict(input_image):
 
 iface = gr.Interface(
     fn=predict, 
-    inputs=gr.Image(shape=(512,512)), 
+    inputs=[
+        gr.Image(shape=(512,512)),
+         gr.inputs.Radio(MODELS_TYPE)
+    ], 
     outputs=gr.Image(shape=(512,512)),
     examples=[
-        ["demo_imgs/fake.jpg"] # use real image
+        ["demo_imgs/fake.jpg", MODELS_TYPE[0]] # use real image
     ],
     title="DTM Estimation",
     description="This demo predict a DTM..."