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Update app.py
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app.py
CHANGED
@@ -13,10 +13,47 @@ MAX_IMAGE_SIZE = 2048
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pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16, revision="refs/pr/4").to("cuda")
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@spaces.GPU
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def infer(edit_images, prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
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print(edit_images)
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image = edit_images["background"]
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mask = edit_images["layers"][0]
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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@@ -41,7 +78,7 @@ examples = [
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css="""
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#col-container {
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margin: 0 auto;
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max-width:
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}
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"""
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@@ -70,7 +107,7 @@ with gr.Blocks(css=css) as demo:
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placeholder="Enter your prompt",
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container=False,
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)
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run_button = gr.Button("Run"
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result = gr.Image(label="Result", show_label=False)
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@@ -94,6 +131,7 @@ with gr.Blocks(css=css) as demo:
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=1024,
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)
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height = gr.Slider(
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@@ -102,6 +140,7 @@ with gr.Blocks(css=css) as demo:
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=1024,
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)
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with gr.Row():
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pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16, revision="refs/pr/4").to("cuda")
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def calculate_optimal_dimensions(image: Image.Image):
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# Extract the original dimensions
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original_width, original_height = image.size
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# Set constants
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MIN_ASPECT_RATIO = 9 / 16
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MAX_ASPECT_RATIO = 16 / 9
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FIXED_DIMENSION = 1024
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# Calculate the aspect ratio of the original image
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original_aspect_ratio = original_width / original_height
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# Determine which dimension to fix
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if original_aspect_ratio > 1: # Wider than tall
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width = FIXED_DIMENSION
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height = round(FIXED_DIMENSION / original_aspect_ratio)
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else: # Taller than wide
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height = FIXED_DIMENSION
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width = round(FIXED_DIMENSION * original_aspect_ratio)
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# Ensure dimensions are multiples of 8
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width = (width // 8) * 8
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height = (height // 8) * 8
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# Enforce aspect ratio limits
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calculated_aspect_ratio = width / height
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if calculated_aspect_ratio > MAX_ASPECT_RATIO:
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width = (height * MAX_ASPECT_RATIO // 8) * 8
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elif calculated_aspect_ratio < MIN_ASPECT_RATIO:
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height = (width / MIN_ASPECT_RATIO // 8) * 8
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# Ensure width and height remain above the minimum dimensions
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width = max(width, 576) if width == FIXED_DIMENSION else width
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height = max(height, 576) if height == FIXED_DIMENSION else height
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return width, height
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@spaces.GPU
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def infer(edit_images, prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
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image = edit_images["background"]
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width, height = calculate_optimal_dimensions(image)
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mask = edit_images["layers"][0]
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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css="""
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#col-container {
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margin: 0 auto;
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max-width: 1000px;
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}
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"""
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placeholder="Enter your prompt",
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container=False,
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)
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run_button = gr.Button("Run")
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result = gr.Image(label="Result", show_label=False)
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=1024,
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visible=False
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)
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height = gr.Slider(
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maximum=MAX_IMAGE_SIZE,
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step=32,
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value=1024,
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visible=False
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)
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with gr.Row():
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