update

app.py

@@ -17,6 +17,12 @@ from time import time
 MAX_SEED = np.iinfo(np.int32).max
 device = "cuda"
 
+
+def check_input_image(input_image):
+    if input_image is None:
+        raise gr.Error("No image uploaded!")
+
+
 def clear_image():
     return None
 
@@ -86,13 +92,10 @@ def image_generation(input_image, quality, random_perturbation, sigma, dimension
     generator, id_model, pose_model, quality_model = initialize_models()
 
     generated_images = []
-    if input_image is None:
-        raise gr.Error("No image uploaded!")
-    else:
-        input_image = np.transpose(input_image, (2, 0, 1))
-        input_image = torch.from_numpy(input_image).unsqueeze(0).float().to(device)
-        input_image.div_(255).sub_(0.5).div_(0.5)
-        feature = id_model(input_image).clone().detach().cpu().numpy()
+    input_image = np.transpose(input_image, (2, 0, 1))
+    input_image = torch.from_numpy(input_image).unsqueeze(0).float().to(device)
+    input_image.div_(255).sub_(0.5).div_(0.5)
+    feature = id_model(input_image).clone().detach().cpu().numpy()
 
     if not random_perturbation:
         features = []
@@ -175,7 +178,7 @@ def main():
 
         gr.Markdown(title)
         gr.Markdown(description)
-        with gr.Row():
+        with gr.Row(variant="panel"):
             with gr.Column():
                 image_file = gr.Image(label="Upload an image (optional)", type="filepath")
 
@@ -243,7 +246,7 @@ def main():
             fn=clear_image,
             inputs=[],
             outputs=[gallery]
-        ).then(
+        ).then(fn=check_input_image, inputs=[image_file]).success(
             fn=generating,
             inputs=[],
             outputs=[generation_time]