This PR allows to automatically change the seed

app.py

@@ -3,9 +3,12 @@ import os
 from glob import glob
 from diffusers.utils import load_image
 import spaces
+import random
 from panna.pipeline import PipelineSVDUpscale
 
 
+max_64_bit_int = 1_000_000
+
 model = PipelineSVDUpscale(upscaler="instruct_ir")
 example_files = []
 root_url = "https://huggingface.co/spaces/multimodalart/stable-video-diffusion/resolve/main/images"
@@ -19,7 +22,10 @@ title = ("# [Stable Video Diffusion](ttps://huggingface.co/stabilityai/stable-vi
 
 
 @spaces.GPU(duration=120)
-def infer(init_image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed):
+def infer(init_image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed, randomize_seed):
+    if randomize_seed:
+        seed = random.randint(0, max_64_bit_int)
+        
     base_count = len(glob(os.path.join(tmp_output_dir, "*.mp4")))
     video_path = os.path.join(tmp_output_dir, f"{base_count:06d}.mp4")
     model(
@@ -41,19 +47,20 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             image = gr.Image(label="Upload your image", type="pil")
-            run_button = gr.Button("Generate")
-        video = gr.Video()
+            run_button = gr.Button(value="Generate", variant="primary")
+        video = gr.Video(autoplay=True)
     with gr.Accordion("Advanced options", open=False):
         upscaler_prompt = gr.Text("Correct the motion blur in this image so it is more clear", label="Prompt for upscaler", show_label=False, max_lines=1, placeholder="Enter your prompt", container=False)
-        seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0)
         num_frames = gr.Slider(label="Number of frames", minimum=1, maximum=100, step=1, value=25)
         motion_bucket_id = gr.Slider(label="Motion bucket id", minimum=1, maximum=255, step=1, value=127)
         noise_aug_strength = gr.Slider(label="Noise strength", minimum=0, maximum=1, step=0.01, value=0.02)
         fps = gr.Slider(label="Frames per second", minimum=5, maximum=30, step=1, value=7)
         decode_chunk_size = gr.Slider(label="Decode chunk size", minimum=1, maximum=25, step=1, value=7)
+        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+        seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0)
     run_button.click(
         fn=infer,
-        inputs=[image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed],
+        inputs=[image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed, randomize_seed],
         outputs=[video]
     )
     gr.Examples(examples=examples, inputs=image)