Default value

app.py

@@ -1066,7 +1066,6 @@ def worker_video(input_video, end_frame, end_stillness, prompts, n_prompt, seed,
             total_context_frames = num_4x_frames + num_2x_frames + effective_clean_frames
             total_context_frames = min(total_context_frames, available_frames)  # 20250507 pftq: Edge case for <=1 sec videos
 
-            post_frames = 100 # Single frame for end_latent, otherwise padding causes still image
             indices = torch.arange(0, 1 + num_4x_frames + num_2x_frames + effective_clean_frames + adjusted_latent_frames + ((latent_padding_size + 1 + local_end_stillness) if end_latent is not None else 0)).unsqueeze(0) # 20250507 pftq: latent_window_size to adjusted_latent_frames for edge case for <=1 sec videos
             clean_latent_indices_start, clean_latent_4x_indices, clean_latent_2x_indices, clean_latent_1x_indices, latent_indices, blank_indices, clean_latent_indices_post = indices.split(
                 [1, num_4x_frames, num_2x_frames, effective_clean_frames, adjusted_latent_frames, latent_padding_size if end_latent is not None else 0, (1 + local_end_stillness) if end_latent is not None else 0], dim=1 # 20250507 pftq: latent_window_size to adjusted_latent_frames for edge case for <=1 sec videos
@@ -1539,7 +1538,7 @@ with block:
                 n_prompt = gr.Textbox(label="Negative Prompt", value="Missing arm, long hand, unrealistic position, impossible contortion, visible bone, muscle contraction, poorly framed, blurred, blurry, over-smooth", info='Requires using normal CFG (undistilled) instead of Distilled (set Distilled=1 and CFG > 1).')
 
                 fps_number = gr.Slider(label="Frame per seconds", info="The model is trained for 30 fps so other fps may generate weird results", minimum=10, maximum=60, value=30, step=1)
-                end_stillness = gr.Slider(label="End stillness", minimum=0, maximum=100, value=1, step=1, info='0=Realistic end; >0=Matches exactly the end image (but the time seems to freeze)')
+                end_stillness = gr.Slider(label="End stillness", minimum=0, maximum=100, value=0, step=1, info='0=Realistic end; >0=Matches exactly the end image (but the time seems to freeze)')
 
                 latent_window_size = gr.Slider(label="Latent Window Size", minimum=1, maximum=33, value=9, step=1, info='Generate more frames at a time (larger chunks). Less degradation and better blending but higher VRAM cost. Should not change.')
                 steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=30, step=1, info='Increase for more quality, especially if using high non-distilled CFG. If your animation has very few motion, you may have brutal brightness change; this can be fixed increasing the steps.')