Update demo_gradio.py

demo_gradio.py

@@ -100,7 +100,7 @@ os.makedirs(outputs_folder, exist_ok=True)
 
 
 @torch.no_grad()
-def worker(input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache):
+def worker(input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache, mp4_crf):
     total_latent_sections = (total_second_length * 30) / (latent_window_size * 4)
     total_latent_sections = int(max(round(total_latent_sections), 1))
 
@@ -295,7 +295,7 @@ def worker(input_image, prompt, n_prompt, seed, total_second_length, latent_wind
 
             output_filename = os.path.join(outputs_folder, f'{job_id}_{total_generated_latent_frames}.mp4')
 
-            save_bcthw_as_mp4(history_pixels, output_filename, fps=30)
+            save_bcthw_as_mp4(history_pixels, output_filename, fps=30, crf=mp4_crf)
 
             print(f'Decoded. Current latent shape {real_history_latents.shape}; pixel shape {history_pixels.shape}')
 
@@ -315,7 +315,7 @@ def worker(input_image, prompt, n_prompt, seed, total_second_length, latent_wind
     return
 
 
-def process(input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache):
+def process(input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache, mp4_crf):
     global stream
     assert input_image is not None, 'No input image!'
 
@@ -323,7 +323,7 @@ def process(input_image, prompt, n_prompt, seed, total_second_length, latent_win
 
     stream = AsyncStream()
 
-    async_run(worker, input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache)
+    async_run(worker, input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache, mp4_crf)
 
     output_filename = None
 
@@ -385,13 +385,18 @@ with block:
 
                 gpu_memory_preservation = gr.Slider(label="GPU Inference Preserved Memory (GB) (larger means slower)", minimum=6, maximum=128, value=6, step=0.1, info="Set this number to a larger value if you encounter OOM. Larger value causes slower speed.")
 
+                mp4_crf = gr.Slider(label="MP4 Compression", minimum=0, maximum=100, value=16, step=1, info="Lower means better quality. 0 is uncompressed. Change to 16 if you get black outputs. ")
+
         with gr.Column():
             preview_image = gr.Image(label="Next Latents", height=200, visible=False)
             result_video = gr.Video(label="Finished Frames", autoplay=True, show_share_button=False, height=512, loop=True)
             gr.Markdown('Note that the ending actions will be generated before the starting actions due to the inverted sampling. If the starting action is not in the video, you just need to wait, and it will be generated later.')
             progress_desc = gr.Markdown('', elem_classes='no-generating-animation')
             progress_bar = gr.HTML('', elem_classes='no-generating-animation')
-    ips = [input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache]
+
+    gr.HTML('<div style="text-align:center; margin-top:20px;">Share your results and find ideas at the <a href="https://x.com/search?q=framepack&f=live" target="_blank">FramePack Twitter (X) thread</a></div>')
+
+    ips = [input_image, prompt, n_prompt, seed, total_second_length, latent_window_size, steps, cfg, gs, rs, gpu_memory_preservation, use_teacache, mp4_crf]
     start_button.click(fn=process, inputs=ips, outputs=[result_video, preview_image, progress_desc, progress_bar, start_button, end_button])
     end_button.click(fn=end_process)
 
@@ -401,4 +406,4 @@ block.launch(
     server_port=args.port,
     share=args.share,
     inbrowser=args.inbrowser,
-)
+)