multimodalart HF staff commited on
Commit
f1c3cc1
1 Parent(s): 9778625

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +14 -13
app.py CHANGED
@@ -9,7 +9,7 @@ import numpy as np
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  import cv2
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  from PIL import Image
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  from diffusers.utils import load_image
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- from diffusers.utils import export_to_gif
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  import random
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  # load pipelines
@@ -21,7 +21,7 @@ pipe = FluxPipeline.from_pretrained(base_model,
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  torch_dtype=torch.bfloat16)
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  pipe.transformer.to(memory_format=torch.channels_last)
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- pipe.transformer = torch.compile(pipe.transformer, mode="max-autotune", fullgraph=True)
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  # pipe.enable_model_cpu_offload()
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  clip_slider = CLIPSliderFlux(pipe, device=torch.device("cuda"))
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@@ -102,7 +102,7 @@ def generate(prompt,
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  post_generation_slider_update = gr.update(label=comma_concepts_x, value=0, minimum=scale_min, maximum=scale_max, interactive=True)
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  avg_diff_x = avg_diff.cpu()
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- return x_concept_1,x_concept_2, avg_diff_x, export_to_gif(images, "clip.gif", fps=5), canvas, images, images[scale_middle], post_generation_slider_update, seed
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  def update_pre_generated_images(slider_value, total_images):
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  number_images = len(total_images)
@@ -134,7 +134,7 @@ intro = """
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  </p>
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  """
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  css='''
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- #strip, #gif{max-height: 170px; min-height: 65px}
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  #strip img{object-fit: cover}
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  '''
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  examples = [["a dog in the park", "winter", "summer", 1.5], ["a house", "USA suburb", "Europe", 2.5], ["a tomato", "rotten", "super fresh", 2.5]]
@@ -161,15 +161,16 @@ with gr.Blocks(css=css) as demo:
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  submit = gr.Button("Generate directions")
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  with gr.Column():
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- with gr.Group(elem_id="group"):
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- post_generation_image = gr.Image(label="Generated Images", type="filepath")
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- post_generation_slider = gr.Slider(minimum=-10, maximum=10, value=0, step=1, label="From 1st to 2nd direction")
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- with gr.Row():
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- with gr.Column(scale=4, min_width=50):
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- image_seq = gr.Image(label="Strip", elem_id="strip", height=65)
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-
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- with gr.Column(scale=2, min_width=50):
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- output_image = gr.Image(label="Gif", elem_id="gif")
 
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  with gr.Accordion(label="Advanced options", open=False):
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  interm_steps = gr.Slider(label = "Num of intermediate images", minimum=3, value=7, maximum=65, step=2)
 
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  import cv2
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  from PIL import Image
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  from diffusers.utils import load_image
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+ from diffusers.utils import export_to_video
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  import random
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  # load pipelines
 
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  torch_dtype=torch.bfloat16)
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  pipe.transformer.to(memory_format=torch.channels_last)
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+ # pipe.transformer = torch.compile(pipe.transformer, mode="max-autotune", fullgraph=True)
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  # pipe.enable_model_cpu_offload()
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  clip_slider = CLIPSliderFlux(pipe, device=torch.device("cuda"))
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  post_generation_slider_update = gr.update(label=comma_concepts_x, value=0, minimum=scale_min, maximum=scale_max, interactive=True)
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  avg_diff_x = avg_diff.cpu()
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+ return x_concept_1,x_concept_2, avg_diff_x, export_to_video(images, f"{uuid.uuid4()}.mp4", fps=5), canvas, images, images[scale_middle], post_generation_slider_update, seed
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  def update_pre_generated_images(slider_value, total_images):
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  number_images = len(total_images)
 
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  </p>
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  """
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  css='''
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+ #strip, #video{max-height: 170px; min-height: 65px}
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  #strip img{object-fit: cover}
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  '''
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  examples = [["a dog in the park", "winter", "summer", 1.5], ["a house", "USA suburb", "Europe", 2.5], ["a tomato", "rotten", "super fresh", 2.5]]
 
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  submit = gr.Button("Generate directions")
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  with gr.Column():
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+ output_image = gr.Video(label="Looping video", elem_id="video", loop=True, autoplay=True)
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+ #with gr.Row():
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+
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+ with gr.Column(scale=4, min_width=50):
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+ image_seq = gr.Image(label="Strip", elem_id="strip", height=65)
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+
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+ with gr.Column(scale=2, min_width=50):
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+ with gr.Group(elem_id="group"):
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+ post_generation_image = gr.Image(label="Generated Images", type="filepath")
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+ post_generation_slider = gr.Slider(minimum=-10, maximum=10, value=0, step=1, label="From 1st to 2nd direction")
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  with gr.Accordion(label="Advanced options", open=False):
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  interm_steps = gr.Slider(label = "Num of intermediate images", minimum=3, value=7, maximum=65, step=2)