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Runtime error
Runtime error
LeoXing1996
commited on
Commit
•
62ab16e
1
Parent(s):
0f3562d
return state for examples
Browse files- app-huggingface.py +126 -29
app-huggingface.py
CHANGED
@@ -37,7 +37,8 @@ def add_text(gif_file: str, mp4_file: str, text_index: int):
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except EOFError:
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pass
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-
text = ['Happy New Year!', 'Happy New Year!',
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size = [36, 36, 36, 36][text_index]
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for i, frame in enumerate(frames):
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@@ -55,6 +56,7 @@ def add_text(gif_file: str, mp4_file: str, text_index: int):
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mp4_file = convert_gif_to_mp4(gif_file, mp4_file)
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return gif_file, mp4_file
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css = """
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.toolbutton {
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margin-buttom: 0em 0em 0em 0em;
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@@ -255,6 +257,83 @@ class AnimateController:
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return n_prompt, ip_adapter_scale
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def animate(
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self,
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init_img,
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motion_scale,
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@@ -269,17 +348,11 @@ class AnimateController:
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with_text=False,
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text_idx=0,
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progress=gr.Progress(),
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-
):
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global sample_idx
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print(example_img)
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-
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if init_img is None:
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-
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gr.Warning('Please upload image or use example images.')
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else:
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gr.Info('Use exmaple image for fast try!')
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init_img = np.array(Image.open(example_img))
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if seed_textbox != -1 and seed_textbox != "":
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torch.manual_seed(int(seed_textbox))
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@@ -339,11 +412,13 @@ class AnimateController:
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add_text(save_sample_path_gif, save_sample_path_mp4, text_idx)
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sample_idx += 1
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# return (save_sample_path_mp4,
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# gr.update(link=f'file/{save_sample_path_mp4}'),
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# gr.update(link=f'file/{save_sample_path_gif}'))
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return (save_sample_path_mp4,
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[save_sample_path_mp4, save_sample_path_gif]
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controller = AnimateController()
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@@ -472,7 +547,8 @@ def ui():
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result_video = gr.Video(
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label="Generated Animation", interactive=False)
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with gr.Row():
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download = gr.Files(
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generate_button.click(
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fn=controller.animate,
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@@ -486,12 +562,11 @@ def ui():
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seed_textbox,
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ip_adapter_scale,
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style_dropdown,
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# None,
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],
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outputs=[result_video, download])
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default_1.click(
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fn=controller.
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inputs=[
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init_img,
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default_motion,
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@@ -506,9 +581,16 @@ def ui():
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with_wishes,
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default_1_idx,
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],
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outputs=[
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default_2.click(
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fn=controller.
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inputs=[
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init_img,
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default_motion,
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@@ -523,9 +605,16 @@ def ui():
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with_wishes,
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default_2_idx,
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],
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outputs=[
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default_3.click(
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fn=controller.
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inputs=[
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init_img,
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default_motion,
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@@ -540,9 +629,16 @@ def ui():
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with_wishes,
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default_3_idx,
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],
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outputs=[
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default_4.click(
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fn=controller.
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inputs=[
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init_img,
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default_motion,
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@@ -557,13 +653,14 @@ def ui():
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with_wishes,
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default_4_idx,
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],
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outputs=[
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-
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-
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-
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-
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-
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def create_example(input_list):
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return gr.Examples(
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except EOFError:
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pass
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+
text = ['Happy New Year!', 'Happy New Year!',
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+
'Happy New Year!', 'Happy New Year!'][text_index]
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size = [36, 36, 36, 36][text_index]
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for i, frame in enumerate(frames):
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mp4_file = convert_gif_to_mp4(gif_file, mp4_file)
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return gif_file, mp4_file
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+
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css = """
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.toolbutton {
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margin-buttom: 0em 0em 0em 0em;
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return n_prompt, ip_adapter_scale
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def animate(
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self,
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init_img,
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motion_scale,
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prompt_textbox,
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negative_prompt_textbox,
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sample_step_slider,
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cfg_scale_slider,
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seed_textbox,
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ip_adapter_scale,
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style,
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progress=gr.Progress(),
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):
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+
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global sample_idx
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if init_img is None:
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gr.Warning('Please upload image or use example images.')
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if seed_textbox != -1 and seed_textbox != "":
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torch.manual_seed(int(seed_textbox))
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seed = int(seed_textbox)
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else:
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seed = torch.initial_seed()
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generator = torch.Generator(device='cuda')
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generator.manual_seed(seed)
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seed_everything(seed)
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print(f'Seed: {seed}')
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pipeline = self.pipeline_dict[style]
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init_img, h, w = preprocess_img(init_img)
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print(f'img size: {h, w}')
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sample = pipeline(
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image=init_img,
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prompt=prompt_textbox,
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negative_prompt=negative_prompt_textbox,
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generator=generator,
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num_inference_steps=sample_step_slider,
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guidance_scale=cfg_scale_slider,
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width=w,
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height=h,
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video_length=16,
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mask_sim_template_idx=motion_scale - 1,
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ip_adapter_scale=ip_adapter_scale,
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progress_fn=progress,
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).videos
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save_sample_path_mp4 = os.path.join(
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self.savedir_sample, f"{sample_idx}.mp4")
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save_sample_path_gif = os.path.join(
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self.savedir_sample, f"{sample_idx}.gif")
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save_videos_grid(sample, save_sample_path_mp4)
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save_videos_grid(sample, save_sample_path_gif)
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sample_config = {
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"prompt": prompt_textbox,
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"n_prompt": negative_prompt_textbox,
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"num_inference_steps": sample_step_slider,
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"guidance_scale": cfg_scale_slider,
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"width": w,
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"height": h,
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"seed": seed,
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"motion": motion_scale,
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}
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print(sample_config)
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json_str = json.dumps(sample_config, indent=4)
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with open(os.path.join(self.savedir, "logs.json"), "a") as f:
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f.write(json_str)
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f.write("\n\n")
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sample_idx += 1
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return (save_sample_path_mp4,
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[save_sample_path_mp4, save_sample_path_gif])
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+
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def animate_example(
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self,
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init_img,
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motion_scale,
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with_text=False,
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text_idx=0,
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progress=gr.Progress(),
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+
):
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global sample_idx
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if init_img is None:
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+
gr.Warning('Please upload image or use example images.')
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if seed_textbox != -1 and seed_textbox != "":
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torch.manual_seed(int(seed_textbox))
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add_text(save_sample_path_gif, save_sample_path_mp4, text_idx)
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sample_idx += 1
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return (save_sample_path_mp4,
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[save_sample_path_mp4, save_sample_path_gif],
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example_img,
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seed,
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motion_scale,
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cfg_scale_slider,
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)
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controller = AnimateController()
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result_video = gr.Video(
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label="Generated Animation", interactive=False)
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with gr.Row():
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download = gr.Files(
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file_types=['gif', 'mp4'], label='Donwload Output')
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generate_button.click(
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fn=controller.animate,
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seed_textbox,
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ip_adapter_scale,
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style_dropdown,
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],
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outputs=[result_video, download])
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default_1.click(
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+
fn=controller.animate_example,
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inputs=[
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init_img,
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default_motion,
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with_wishes,
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default_1_idx,
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],
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+
outputs=[
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result_video,
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download,
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example_img,
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+
default_seed,
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default_motion,
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default_cfg,
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])
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default_2.click(
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fn=controller.animate_example,
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inputs=[
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init_img,
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default_motion,
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with_wishes,
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default_2_idx,
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],
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+
outputs=[
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result_video,
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+
download,
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example_img,
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default_seed,
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default_motion,
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default_cfg,
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])
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default_3.click(
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fn=controller.animate_example,
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inputs=[
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init_img,
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default_motion,
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with_wishes,
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default_3_idx,
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],
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+
outputs=[
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result_video,
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download,
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example_img,
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default_seed,
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default_motion,
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default_cfg,
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])
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default_4.click(
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fn=controller.animate_example,
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inputs=[
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init_img,
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default_motion,
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with_wishes,
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default_4_idx,
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],
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+
outputs=[
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result_video,
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download,
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example_img,
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default_seed,
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default_motion,
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default_cfg,
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])
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def create_example(input_list):
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return gr.Examples(
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