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Update app.py
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app.py
CHANGED
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@@ -58,13 +58,13 @@ model_num_of_layers = {
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}
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def generate_images(prompt, model, seed):
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seed = random.randint(0, MAX_SEED) if seed == -1 else seed
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print('calling diffusion lens with model:', model, 'and seed:', seed)
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gr.Info('Generating images from intermediate layers..')
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all_images = [] # Initialize a list to store all images
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max_num_of_layers = model_num_of_layers[model]
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for skip_layers in range(max_num_of_layers - 1, -1, -1):
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# Pass the model and seed to the get_images function
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images = get_images(prompt, skip_layers=skip_layers, model=model, seed=seed)
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all_images.append((images[0], f'layer_{max_num_of_layers - skip_layers}'))
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@@ -106,10 +106,19 @@ with gr.Blocks() as demo:
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label="Seed Value",
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)
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inputs = [
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prompt,
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model,
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seed,
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]
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}
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def generate_images(prompt, model, seed, skip):
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seed = random.randint(0, MAX_SEED) if seed == -1 else seed
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print('calling diffusion lens with model:', model, 'and seed:', seed)
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gr.Info('Generating images from intermediate layers..')
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all_images = [] # Initialize a list to store all images
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max_num_of_layers = model_num_of_layers[model]
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for skip_layers in range(max_num_of_layers - 1, -1, -1 * skip):
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# Pass the model and seed to the get_images function
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images = get_images(prompt, skip_layers=skip_layers, model=model, seed=seed)
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all_images.append((images[0], f'layer_{max_num_of_layers - skip_layers}'))
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label="Seed Value",
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)
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skip = gr.Slider(
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minimum=0,
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maximum=6,
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value=4,
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step=1,
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label="Number of layers to skip between each generaion",
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)
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inputs = [
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prompt,
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model,
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seed,
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skip,
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]
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