Update app.py

app.py

@@ -16,6 +16,8 @@ from huggingface_hub import hf_hub_download
 
 #gradio.helpers.CACHED_FOLDER = '/data/cache'
 
+SECRET_TOKEN = os.getenv('SECRET_TOKEN', 'default_secret')
+
 pipe = StableVideoDiffusionPipeline.from_pretrained(
     "stabilityai/stable-video-diffusion-img2vid-xt", torch_dtype=torch.float16, variant="fp16"
 )
@@ -36,7 +38,14 @@ def sample(
     decoding_t: int = 3,  # Number of frames decoded at a time! This eats most VRAM. Reduce if necessary.
     device: str = "cuda",
     output_folder: str = "outputs",
+    secret_token: string = "",
 ):
+    if secret_token != SECRET_TOKEN:
+        raise gr.Error(
+            f'Invalid secret token. Please fork the original space if you want to use it for yourself.')
+
+    image = resize_image(image)
+    
     if image.mode == "RGBA":
         image = image.convert("RGB")
         
@@ -89,6 +98,11 @@ with gr.Blocks() as demo:
   gr.Markdown('''# Community demo for Stable Video Diffusion - Img2Vid - XT ([model](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt), [paper](https://stability.ai/research/stable-video-diffusion-scaling-latent-video-diffusion-models-to-large-datasets), [stability's ui waitlist](https://stability.ai/contact))
 #### Research release ([_non-commercial_](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt/blob/main/LICENSE)): generate `4s` vid from a single image at (`25 frames` at `6 fps`). this demo uses [🧨 diffusers for low VRAM and fast generation](https://huggingface.co/docs/diffusers/main/en/using-diffusers/svd).
   ''')
+    secret_token = gr.Text(
+        label='Secret Token',
+        max_lines=1,
+        placeholder='Enter your secret token',
+    )
   with gr.Row():
     with gr.Column():
         image = gr.Image(label="Upload your image", type="pil")
@@ -100,25 +114,8 @@ with gr.Blocks() as demo:
       motion_bucket_id = gr.Slider(label="Motion bucket id", info="Controls how much motion to add/remove from the image", value=127, minimum=1, maximum=255)
       fps_id = gr.Slider(label="Frames per second", info="The length of your video in seconds will be 25/fps", value=6, minimum=5, maximum=30)
       
-  image.upload(fn=resize_image, inputs=image, outputs=image, queue=False)
-  generate_btn.click(fn=sample, inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id], outputs=[video, seed], api_name="video")
-  gr.Examples(
-    examples=[
-        "images/blink_meme.png",
-        "images/confused2_meme.png",
-        "images/disaster_meme.png",
-        "images/distracted_meme.png",
-        "images/hide_meme.png",
-        "images/nazare_meme.png",
-        "images/success_meme.png",
-        "images/willy_meme.png",
-        "images/wink_meme.png"
-    ],
-    inputs=image,
-    outputs=[video, seed],
-    fn=sample,
-    cache_examples=True,
-  )
+  # image.upload(fn=resize_image, inputs=image, outputs=image, queue=False)
+  generate_btn.click(fn=sample, inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id, secret_token], outputs=[video, seed], api_name="video")
 
 if __name__ == "__main__":
     demo.queue(max_size=20)