Alternatively, try our GitHub code on your GPU.
""") with gr.Row(): with gr.Column(): with gr.Accordion('Input Video', open=True): # user_input_video = gr.File(label='Input Source Video') user_input_video = gr.Video(label='Input Source Video', source='upload', type='numpy', format="mp4", visible=True).style(height="auto") with gr.Accordion('Temporal Crop offset and Sampling Stride', open=False): n_sample_frame = gr.Slider(label='Number of Frames', minimum=0, maximum=32, step=1, value=8) stride = gr.Slider(label='Temporal stride', minimum=0, maximum=20, step=1, value=1) start_sample_frame = gr.Number(label='Start frame in the video', value=0, precision=0) with gr.Accordion('Spatial Crop offset', open=False): left_crop = gr.Number(label='Left crop', value=0, precision=0) right_crop = gr.Number(label='Right crop', value=0, precision=0) top_crop = gr.Number(label='Top crop', value=0, precision=0) bottom_crop = gr.Number(label='Bottom crop', value=0, precision=0) offset_list = [ left_crop, right_crop, top_crop, bottom_crop, ] ImageSequenceDataset_list = [ start_sample_frame, n_sample_frame, stride ] + offset_list # model_id = gr.Dropdown( # label='Model ID', # choices=[ # 'CompVis/stable-diffusion-v1-4', # # add shape editing ckpt here # ], # value='CompVis/stable-diffusion-v1-4') with gr.Accordion('Text Prompt', open=True): # source_prompt = gr.Textbox(label='Source Prompt', # info='A good prompt describes each frame and most objects in video. Especially, it has the object or attribute that we want to edit or preserve.', # max_lines=1, # placeholder='Example: "a silver jeep driving down a curvy road in the countryside"', # value='a silver jeep driving down a curvy road in the countryside') target_prompt = gr.Textbox(label='Target Prompt', info='A reasonable composition of video may achieve better results(e.g., "sunflower" video with "Van Gogh" prompt is better than "sunflower" with "Monet")', max_lines=1, placeholder='Example: "watercolor painting of a silver jeep driving down a curvy road in the countryside"', value='watercolor painting of a silver jeep driving down a curvy road in the countryside') run_button = gr.Button('Generate') with gr.Column(): result = gr.Video(label='Result') # result.style(height=512, width=512) # with gr.Accordion('FateZero Parameters for attention fusing', open=True): # cross_replace_steps = gr.Slider(label='Cross-att replace steps', # info='More steps, replace more cross attention to preserve semantic layout.', # minimum=0.0, # maximum=1.0, # step=0.1, # value=0.7) # self_replace_steps = gr.Slider(label='Self-att replace steps', # info='More steps, replace more spatial-temporal self-attention to preserve geometry and motion.', # minimum=0.0, # maximum=1.0, # step=0.1, # value=0.7) # enhance_words = gr.Textbox(label='Enhanced words', # info='Amplify the target-words cross attention', # max_lines=1, # placeholder='Example: "watercolor "', # value='watercolor') # enhance_words_value = gr.Slider(label='Target cross-att amplification', # info='larger value, more elements of target words', # minimum=0.0, # maximum=20.0, # step=1, # value=10) with gr.Accordion('DDIM Parameters', open=True): num_steps = gr.Slider(label='Number of Steps', info='larger value has better editing capacity, but takes more time and memory.', minimum=0, maximum=50, step=1, value=50) guidance_scale = gr.Slider(label='CFG Scale', minimum=0, maximum=50, step=0.1, value=12.5) with gr.Row(): from example import style_example examples = style_example inputs = [ user_input_video, target_prompt, num_steps, guidance_scale, *ImageSequenceDataset_list ] target_prompt.submit(fn=pipe.run, inputs=inputs, outputs=result) run_button.click(fn=pipe.run, inputs=inputs, outputs=result) demo.queue().launch(share=False, server_name='0.0.0.0', server_port=80)