scaling to speedup

app.py

@@ -9,6 +9,7 @@ from models.modelNetA import Generator as GA
 from models.modelNetB import Generator as GB
 from models.modelNetC import Generator as GC
 
+scale_size = 128
 # load model
 modeltype2path = {
     'ModelA': 'DTM_exp_train10%_model_a/g-best.pth',
@@ -59,8 +60,8 @@ def predict(input_image, model_name):
 iface = gr.Interface(
     fn=predict, 
     inputs=[
-        gr.Image(shape=(512,512)),
-         gr.inputs.Radio(MODELS_TYPE)
+        gr.Image(shape=(scale_size,scale_size)),
+        gr.inputs.Radio(MODELS_TYPE)
     ], 
     outputs=[
         gr.Text(),
@@ -71,6 +72,6 @@ iface = gr.Interface(
         ["demo_imgs/fake.jpg", MODELS_TYPE[0]] # use real image
     ],
     title="Super Resolution and DTM Estimation",
-    description="This demo predict Super Resolution and (Super Resolution) DTM from a Grayscale image (if RGB we convert it)."
+description=f"This demo predict Super Resolution and (Super Resolution) DTM from a Grayscale image (if RGB we convert it, for demo reason input is scale to {scale_size}x{scale_size})."
 )
 iface.launch()