change discription

app.py

@@ -8,12 +8,13 @@ from huggingface_hub import hf_hub_download
 from models import iresnet
 from sixdrepnet.model import SixDRepNet
 import pixel_generator.vec2face.model_vec2face as model_vec2face
-MAX_SEED = np.iinfo(np.int32).max
 import torch
-import spaces
+import os
+# import spaces
 from time import time
 
 
+MAX_SEED = np.iinfo(np.int32).max
 device = "cuda"
 
 def clear_image():
@@ -80,13 +81,13 @@ def initialize_models():
 
     return generator, id_model, pose_model, quality_model
 
-@spaces.GPU
+# @spaces.GPU
 def image_generation(input_image, quality, random_perturbation, sigma, dimension, progress=gr.Progress()):
     generator, id_model, pose_model, quality_model = initialize_models()
 
     generated_images = []
     if input_image is None:
-        feature = np.random.normal(0, 1.0, (1, 512))
+        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)
@@ -120,7 +121,7 @@ def image_generation(input_image, quality, random_perturbation, sigma, dimension
 
     return generated_images
 
-@spaces.GPU
+# @spaces.GPU
 def process_input(image_input, num1, num2, num3, num4, random_seed, target_quality, random_perturbation, sigma, progress=gr.Progress()):
     # Ensure all dimension numbers are within [0, 512)
     num1, num2, num3, num4 = [max(0, min(int(n), 511)) for n in [num1, num2, num3, num4]]
@@ -168,7 +169,7 @@ def main():
             How to use:<br>
             1. Upload an image with a cropped face image or directly click <b>Submit</b> button, three images will be shown on the right. 
             2. You can control the image quality, image pose, and modify the values in the target dimensions to change the output images. 
-            3. The output results will shown three results of dimension modification or pose images.
+            3. The output results will shown three results of dimension modification or vector perturbation.
             4. Enjoy! 😊
             """
 
@@ -200,14 +201,25 @@ def main():
                     random_perturbation = gr.Checkbox(label="Random Perturbation")
                     sigma = gr.Slider(label="Sigma value", value=0, minimum=0, maximum=1, step=0.1, visible=False)
 
-                submit = gr.Button("Submit", variant="primary")
+                submit = gr.Button("Generate", variant="primary")
+
+                with gr.Row(variant="panel"):
+                    gr.Examples(
+                        examples=[
+                            os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples"))
+                        ],
+                        inputs=[image_file],
+                        label="Examples",
+                        cache_examples=False,
+                        examples_per_page=8
+                    )
 
                 gr.Markdown("""
                             ## Usage tips of Vec2Face
                             - Directly clicking "Submit" button will give you results from a randomly sampled vector. 
                             - If you want to modify more dimensions or change attributes, Code snippets in [Vec2Face repo](https://github.com/HaiyuWu/vec2face) might be helpful.
-                            - For better experience, we suggest you to run code on a GPU machine.
                             """)
+            #     - For better experience, we suggest you to run code on a GPU machine.
 
             with gr.Column():
                 gallery = gr.Image(label="Generated Image")
@@ -282,7 +294,7 @@ def main():
         """
         gr.Markdown(article)
 
-    demo.launch()
+    demo.launch(share=True)
 
 
 if __name__ == "__main__":