Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -11,6 +11,9 @@ pipe.to("cuda")
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pipe_upsample.to("cuda")
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pipe.vae.enable_tiling()
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def round_to_nearest_resolution_acceptable_by_vae(height, width):
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height = height - (height % pipe.vae_temporal_compression_ratio)
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@@ -24,12 +27,16 @@ def generate(prompt,
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steps,
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num_frames,
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seed,
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randomize_seed
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expected_height, expected_width = 768, 1152
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downscale_factor = 2 / 3
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if
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condition1 = LTXVideoCondition(video=image, frame_index=0)
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else:
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condition1 = None
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@@ -43,8 +50,8 @@ def generate(prompt,
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conditions=condition1,
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prompt=prompt,
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negative_prompt=negative_prompt,
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width=downscaled_width,
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height=downscaled_height,
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num_frames=num_frames,
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num_inference_steps=steps,
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decode_timestep = 0.05,
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@@ -55,7 +62,7 @@ def generate(prompt,
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# Part 2. Upscale generated video using latent upsampler with fewer inference steps
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# The available latent upsampler upscales the height/width by 2x
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upscaled_height, upscaled_width = downscaled_height * 2, downscaled_width * 2
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# upscaled_latents = pipe_upsample(
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# latents=latents,
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# output_type="latent"
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@@ -112,6 +119,7 @@ with gr.Blocks(css=css, theme=gr.themes.Ocean()) as demo:
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with gr.Group():
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image = gr.Image(label="")
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prompt = gr.Textbox(label="prompt")
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run_button = gr.Button()
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with gr.Column():
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output = gr.Video(interactive=False)
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@@ -134,7 +142,7 @@ with gr.Blocks(css=css, theme=gr.themes.Ocean()) as demo:
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steps,
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num_frames,
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seed,
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randomize_seed],
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outputs=[output])
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pipe_upsample.to("cuda")
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pipe.vae.enable_tiling()
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 2048
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def round_to_nearest_resolution_acceptable_by_vae(height, width):
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height = height - (height % pipe.vae_temporal_compression_ratio)
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steps,
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num_frames,
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seed,
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randomize_seed,
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t2v, progress=gr.Progress(track_tqdm=True)):
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expected_height, expected_width = 768, 1152
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downscale_factor = 2 / 3
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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if image is not None or t2v:
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condition1 = LTXVideoCondition(video=image, frame_index=0)
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else:
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condition1 = None
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conditions=condition1,
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prompt=prompt,
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negative_prompt=negative_prompt,
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# width=downscaled_width,
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# height=downscaled_height,
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num_frames=num_frames,
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num_inference_steps=steps,
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decode_timestep = 0.05,
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# Part 2. Upscale generated video using latent upsampler with fewer inference steps
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# The available latent upsampler upscales the height/width by 2x
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# upscaled_height, upscaled_width = downscaled_height * 2, downscaled_width * 2
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# upscaled_latents = pipe_upsample(
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# latents=latents,
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# output_type="latent"
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with gr.Group():
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image = gr.Image(label="")
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prompt = gr.Textbox(label="prompt")
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t2v = gr.Checkbox(label="run text-to-video", value=False)
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run_button = gr.Button()
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with gr.Column():
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output = gr.Video(interactive=False)
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steps,
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num_frames,
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seed,
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randomize_seed, t2v],
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outputs=[output])
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