First motion control: fixed camera
#40
by
Fabrice-TIERCELIN
- opened
app.py
CHANGED
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@@ -42,7 +42,8 @@ def animate(
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frame_format: str = "webp",
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version: str = "auto",
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width: int = 1024,
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height: int = 576
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):
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start = time.time()
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@@ -50,9 +51,12 @@ def animate(
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raise gr.Error("Please provide an image to animate.")
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output_folder = "outputs"
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if
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-
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if randomize_seed:
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seed = random.randint(0, max_64_bit_int)
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@@ -64,7 +68,7 @@ def animate(
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version = "svd"
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frames = animate_on_gpu(
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-
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seed,
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motion_bucket_id,
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fps_id,
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@@ -121,7 +125,7 @@ def animate(
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@torch.no_grad()
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@spaces.GPU(duration=180)
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def animate_on_gpu(
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-
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seed: Optional[int] = 42,
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motion_bucket_id: int = 127,
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fps_id: int = 6,
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@@ -134,11 +138,11 @@ def animate_on_gpu(
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generator = torch.manual_seed(seed)
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if version == "dragnuwa":
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return dragnuwaPipe(
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elif version == "svdxt":
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return fps25Pipe(
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else:
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return fps14Pipe(
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def resize_image(image, output_size=(1024, 576)):
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@@ -188,7 +192,8 @@ def reset():
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"webp",
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"auto",
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1024,
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576
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]
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with gr.Blocks() as demo:
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@@ -210,12 +215,13 @@ with gr.Blocks() as demo:
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with gr.Accordion("Advanced options", open=False):
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width = gr.Slider(label="Width", info="Width of the video", value=1024, minimum=256, maximum=1024, step=8)
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height = gr.Slider(label="Height", info="Height of the video", value=576, minimum=256, maximum=576, step=8)
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fps_id = gr.Slider(label="Frames per second", info="The length of your video in seconds will be 25/fps", value=25, minimum=5, maximum=30)
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motion_bucket_id = gr.Slider(label="Motion bucket id", info="Controls how much motion to add/remove from the image", value=127, minimum=1, maximum=255)
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noise_aug_strength = gr.Slider(label="Noise strength", info="The noise to add", value=0.1, minimum=0, maximum=1, step=0.1)
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decoding_t = gr.Slider(label="Decoding", info="Number of frames decoded at a time; this eats more VRAM; reduce if necessary", value=3, minimum=1, maximum=5, step=1)
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video_format = gr.Radio([["*.mp4", "mp4"], ["*.avi", "avi"], ["*.wmv", "wmv"], ["*.mkv", "mkv"], ["*.mov", "mov"], ["*.gif", "gif"]], label="Video format for result", info="File extention", value="mp4", interactive=True)
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frame_format = gr.Radio([["*.webp", "webp"], ["*.png", "png"], ["*.jpeg", "jpeg"], ["*.gif (unanimated)", "gif"], ["*.bmp", "bmp"]], label="Image format for frames", info="File extention", value="webp", interactive=True)
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version = gr.Radio([["Auto", "auto"], ["ππ»ββοΈ SVD (trained on 14 f/s)", "svd"], ["ππ»ββοΈπ¨ SVD-XT (trained on 25 f/s)", "svdxt"], ["DragNUWA (unstable)", "dragnuwa"]], label="Model", info="Trained model", value="auto", interactive=True)
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seed = gr.Slider(label="Seed", value=42, randomize=True, minimum=0, maximum=max_64_bit_int, step=1)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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@@ -242,7 +248,8 @@ with gr.Blocks() as demo:
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frame_format,
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version,
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width,
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height
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], outputs=[
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video_output,
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gif_output,
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@@ -265,16 +272,17 @@ with gr.Blocks() as demo:
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frame_format,
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version,
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width,
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height
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], queue = False, show_progress = False)
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gr.Examples(
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examples=[
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["Examples/Fire.webp", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto", 1024, 576],
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["Examples/Water.png", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto", 1024, 576],
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["Examples/Town.jpeg", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto", 1024, 576]
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],
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inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id, noise_aug_strength, decoding_t, video_format, frame_format, version, width, height],
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outputs=[video_output, gif_output, download_button, gallery, seed, information_msg, reset_btn],
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fn=animate,
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run_on_click=True,
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frame_format: str = "webp",
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version: str = "auto",
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width: int = 1024,
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height: int = 576,
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motion_control: bool = False
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):
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start = time.time()
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raise gr.Error("Please provide an image to animate.")
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output_folder = "outputs"
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image_data = resize_image(image, output_size=(width, height))
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if image_data.mode == "RGBA":
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image_data = image_data.convert("RGB")
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if motion_control:
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image_data = [image_data] * 25
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if randomize_seed:
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seed = random.randint(0, max_64_bit_int)
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version = "svd"
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frames = animate_on_gpu(
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image_data,
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seed,
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motion_bucket_id,
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fps_id,
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@torch.no_grad()
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@spaces.GPU(duration=180)
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def animate_on_gpu(
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image_data: Union[Image, List[Image]],
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seed: Optional[int] = 42,
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motion_bucket_id: int = 127,
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fps_id: int = 6,
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generator = torch.manual_seed(seed)
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if version == "dragnuwa":
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return dragnuwaPipe(image_data, width=width, height=height, decode_chunk_size=decoding_t, generator=generator, motion_bucket_id=motion_bucket_id, noise_aug_strength=noise_aug_strength, num_frames=25).frames[0]
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elif version == "svdxt":
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return fps25Pipe(image_data, width=width, height=height, decode_chunk_size=decoding_t, generator=generator, motion_bucket_id=motion_bucket_id, noise_aug_strength=noise_aug_strength, num_frames=25).frames[0]
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else:
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return fps14Pipe(image_data, width=width, height=height, decode_chunk_size=decoding_t, generator=generator, motion_bucket_id=motion_bucket_id, noise_aug_strength=noise_aug_strength, num_frames=25).frames[0]
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def resize_image(image, output_size=(1024, 576)):
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"webp",
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"auto",
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1024,
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576,
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False
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]
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with gr.Blocks() as demo:
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with gr.Accordion("Advanced options", open=False):
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width = gr.Slider(label="Width", info="Width of the video", value=1024, minimum=256, maximum=1024, step=8)
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height = gr.Slider(label="Height", info="Height of the video", value=576, minimum=256, maximum=576, step=8)
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motion_control = gr.Checkbox(label="Motion control (fixed camera)", info="Fix the camera", value=False)
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video_format = gr.Radio([["*.mp4", "mp4"], ["*.avi", "avi"], ["*.wmv", "wmv"], ["*.mkv", "mkv"], ["*.mov", "mov"], ["*.gif", "gif"]], label="Video format for result", info="File extention", value="mp4", interactive=True)
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frame_format = gr.Radio([["*.webp", "webp"], ["*.png", "png"], ["*.jpeg", "jpeg"], ["*.gif (unanimated)", "gif"], ["*.bmp", "bmp"]], label="Image format for frames", info="File extention", value="webp", interactive=True)
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fps_id = gr.Slider(label="Frames per second", info="The length of your video in seconds will be 25/fps", value=25, minimum=5, maximum=30)
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motion_bucket_id = gr.Slider(label="Motion bucket id", info="Controls how much motion to add/remove from the image", value=127, minimum=1, maximum=255)
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noise_aug_strength = gr.Slider(label="Noise strength", info="The noise to add", value=0.1, minimum=0, maximum=1, step=0.1)
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decoding_t = gr.Slider(label="Decoding", info="Number of frames decoded at a time; this eats more VRAM; reduce if necessary", value=3, minimum=1, maximum=5, step=1)
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version = gr.Radio([["Auto", "auto"], ["ππ»ββοΈ SVD (trained on 14 f/s)", "svd"], ["ππ»ββοΈπ¨ SVD-XT (trained on 25 f/s)", "svdxt"], ["DragNUWA (unstable)", "dragnuwa"]], label="Model", info="Trained model", value="auto", interactive=True)
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seed = gr.Slider(label="Seed", value=42, randomize=True, minimum=0, maximum=max_64_bit_int, step=1)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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frame_format,
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version,
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width,
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height,
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motion_control
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], outputs=[
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video_output,
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gif_output,
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frame_format,
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version,
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width,
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height,
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motion_control
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], queue = False, show_progress = False)
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gr.Examples(
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examples=[
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["Examples/Fire.webp", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto", 1024, 576, False],
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["Examples/Water.png", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto", 1024, 576, False],
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["Examples/Town.jpeg", 42, True, 127, 25, 0.1, 3, "mp4", "png", "auto", 1024, 576, False]
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],
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inputs=[image, seed, randomize_seed, motion_bucket_id, fps_id, noise_aug_strength, decoding_t, video_format, frame_format, version, width, height, motion_control],
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outputs=[video_output, gif_output, download_button, gallery, seed, information_msg, reset_btn],
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fn=animate,
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run_on_click=True,
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