linoyts HF Staff commited on
Commit
d191aca
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verified ·
1 Parent(s): c1ec103

Update app.py

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Files changed (1) hide show
  1. app.py +14 -6
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)
@@ -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 image is not None:
 
 
 
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  condition1 = LTXVideoCondition(video=image, frame_index=0)
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  else:
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  condition1 = None
@@ -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,
@@ -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"
@@ -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)
@@ -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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+
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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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+
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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,
 
62
 
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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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