Update app.py
Browse files
app.py
CHANGED
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@@ -5,6 +5,7 @@ from controlnet_flux import FluxControlNetModel
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from transformer_flux import FluxTransformer2DModel
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from pipeline_flux_controlnet_inpaint import FluxControlNetInpaintingPipeline
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from PIL import Image, ImageDraw
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import spaces
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# Load models
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@@ -21,78 +22,370 @@ pipe = FluxControlNetInpaintingPipeline.from_pretrained(
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pipe.transformer.to(torch.bfloat16)
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pipe.controlnet.to(torch.bfloat16)
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def
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#
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], fill=0)
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return background, mask
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@spaces.GPU
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def inpaint(image,
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image, mask = prepare_image_and_mask(image, width, height, overlap_percentage)
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generator = torch.Generator(device="cuda").manual_seed(42)
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# Run inpainting
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result = pipe(
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prompt=
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height=height,
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width=width,
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control_image=
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control_mask=mask,
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num_inference_steps=num_inference_steps,
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generator=generator,
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controlnet_conditioning_scale=0.9,
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guidance_scale=
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negative_prompt="",
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true_guidance_scale=
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).images[0]
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return
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run_button.click(
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fn=inpaint,
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inputs=[input_image,
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)
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demo.launch()
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from transformer_flux import FluxTransformer2DModel
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from pipeline_flux_controlnet_inpaint import FluxControlNetInpaintingPipeline
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from PIL import Image, ImageDraw
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+
import numpy as np
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import spaces
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# Load models
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pipe.transformer.to(torch.bfloat16)
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pipe.controlnet.to(torch.bfloat16)
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def can_expand(source_width, source_height, target_width, target_height, alignment):
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if alignment in ("Left", "Right") and source_width >= target_width:
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return False
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if alignment in ("Top", "Bottom") and source_height >= target_height:
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return False
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return True
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def prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
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target_size = (width, height)
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# Calculate the scaling factor to fit the image within the target size
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scale_factor = min(target_size[0] / image.width, target_size[1] / image.height)
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new_width = int(image.width * scale_factor)
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new_height = int(image.height * scale_factor)
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# Resize the source image to fit within target size
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source = image.resize((new_width, new_height), Image.LANCZOS)
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# Apply resize option using percentages
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if resize_option == "Full":
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resize_percentage = 100
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elif resize_option == "50%":
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resize_percentage = 50
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elif resize_option == "33%":
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resize_percentage = 33
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elif resize_option == "25%":
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resize_percentage = 25
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else: # Custom
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resize_percentage = custom_resize_percentage
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# Calculate new dimensions based on percentage
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resize_factor = resize_percentage / 100
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new_width = int(source.width * resize_factor)
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new_height = int(source.height * resize_factor)
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# Ensure minimum size of 64 pixels
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new_width = max(new_width, 64)
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new_height = max(new_height, 64)
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# Resize the image
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source = source.resize((new_width, new_height), Image.LANCZOS)
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# Calculate the overlap in pixels based on the percentage
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overlap_x = int(new_width * (overlap_percentage / 100))
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overlap_y = int(new_height * (overlap_percentage / 100))
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# Ensure minimum overlap of 1 pixel
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overlap_x = max(overlap_x, 1)
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overlap_y = max(overlap_y, 1)
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# Calculate margins based on alignment
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if alignment == "Middle":
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margin_x = (target_size[0] - new_width) // 2
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margin_y = (target_size[1] - new_height) // 2
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elif alignment == "Left":
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margin_x = 0
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margin_y = (target_size[1] - new_height) // 2
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elif alignment == "Right":
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margin_x = target_size[0] - new_width
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margin_y = (target_size[1] - new_height) // 2
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elif alignment == "Top":
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margin_x = (target_size[0] - new_width) // 2
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margin_y = 0
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elif alignment == "Bottom":
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margin_x = (target_size[0] - new_width) // 2
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margin_y = target_size[1] - new_height
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# Adjust margins to eliminate gaps
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margin_x = max(0, min(margin_x, target_size[0] - new_width))
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margin_y = max(0, min(margin_y, target_size[1] - new_height))
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# Create a new background image and paste the resized source image
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background = Image.new('RGB', target_size, (255, 255, 255))
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background.paste(source, (margin_x, margin_y))
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# Create the mask
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mask = Image.new('L', target_size, 255)
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mask_draw = ImageDraw.Draw(mask)
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# Calculate overlap areas
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white_gaps_patch = 2
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left_overlap = margin_x + overlap_x if overlap_left else margin_x + white_gaps_patch
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right_overlap = margin_x + new_width - overlap_x if overlap_right else margin_x + new_width - white_gaps_patch
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top_overlap = margin_y + overlap_y if overlap_top else margin_y + white_gaps_patch
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bottom_overlap = margin_y + new_height - overlap_y if overlap_bottom else margin_y + new_height - white_gaps_patch
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if alignment == "Left":
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left_overlap = margin_x + overlap_x if overlap_left else margin_x
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elif alignment == "Right":
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right_overlap = margin_x + new_width - overlap_x if overlap_right else margin_x + new_width
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elif alignment == "Top":
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top_overlap = margin_y + overlap_y if overlap_top else margin_y
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elif alignment == "Bottom":
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bottom_overlap = margin_y + new_height - overlap_y if overlap_bottom else margin_y + new_height
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# Draw the mask
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mask_draw.rectangle([
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(left_overlap, top_overlap),
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(right_overlap, bottom_overlap)
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], fill=0)
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return background, mask
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@spaces.GPU
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def inpaint(image, width, height, overlap_percentage, num_inference_steps, resize_option, custom_resize_percentage, prompt_input, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
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background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom)
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if not can_expand(background.width, background.height, width, height, alignment):
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alignment = "Middle"
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cnet_image = background.copy()
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cnet_image.paste(0, (0, 0), mask)
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final_prompt = f"{prompt_input} , high quality, 4k"
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generator = torch.Generator(device="cuda").manual_seed(42)
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result = pipe(
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prompt=final_prompt,
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height=height,
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width=width,
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control_image=cnet_image,
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control_mask=mask,
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num_inference_steps=num_inference_steps,
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generator=generator,
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controlnet_conditioning_scale=0.9,
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guidance_scale=3.5,
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negative_prompt="",
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true_guidance_scale=3.5
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).images[0]
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result = result.convert("RGBA")
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cnet_image.paste(result, (0, 0), mask)
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return background, cnet_image
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def preview_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
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background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom)
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preview = background.copy().convert('RGBA')
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red_overlay = Image.new('RGBA', background.size, (255, 0, 0, 64))
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red_mask = Image.new('RGBA', background.size, (0, 0, 0, 0))
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red_mask.paste(red_overlay, (0, 0), mask)
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preview = Image.alpha_composite(preview, red_mask)
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return preview
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def clear_result():
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return gr.update(value=None)
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def preload_presets(target_ratio, ui_width, ui_height):
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if target_ratio == "9:16":
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return 720, 1280, gr.update()
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elif target_ratio == "16:9":
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return 1280, 720, gr.update()
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elif target_ratio == "1:1":
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return 1024, 1024, gr.update()
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elif target_ratio == "Custom":
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return ui_width, ui_height, gr.update(open=True)
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def select_the_right_preset(user_width, user_height):
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if user_width == 720 and user_height == 1280:
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return "9:16"
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elif user_width == 1280 and user_height == 720:
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return "16:9"
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elif user_width == 1024 and user_height == 1024:
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return "1:1"
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else:
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return "Custom"
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def toggle_custom_resize_slider(resize_option):
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return gr.update(visible=(resize_option == "Custom"))
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def update_history(new_image, history):
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if history is None:
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history = []
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history.insert(0, new_image)
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return history
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+
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| 205 |
+
css = """
|
| 206 |
+
.gradio-container {
|
| 207 |
+
width: 1200px !important;
|
| 208 |
+
}
|
| 209 |
+
"""
|
| 210 |
+
|
| 211 |
+
title = """<h1 align="center">FLUX Image Outpaint</h1>
|
| 212 |
+
<div align="center">Drop an image you would like to extend, pick your expected ratio and hit Generate.</div>
|
| 213 |
+
"""
|
| 214 |
+
|
| 215 |
+
with gr.Blocks(css=css) as demo:
|
| 216 |
+
with gr.Column():
|
| 217 |
+
gr.HTML(title)
|
| 218 |
+
|
| 219 |
+
with gr.Row():
|
| 220 |
+
with gr.Column():
|
| 221 |
+
input_image = gr.Image(
|
| 222 |
+
type="pil",
|
| 223 |
+
label="Input Image"
|
| 224 |
+
)
|
| 225 |
+
|
| 226 |
+
with gr.Row():
|
| 227 |
+
with gr.Column(scale=2):
|
| 228 |
+
prompt_input = gr.Textbox(label="Prompt (Optional)")
|
| 229 |
+
with gr.Column(scale=1):
|
| 230 |
+
run_button = gr.Button("Generate")
|
| 231 |
+
|
| 232 |
+
with gr.Row():
|
| 233 |
+
target_ratio = gr.Radio(
|
| 234 |
+
label="Expected Ratio",
|
| 235 |
+
choices=["9:16", "16:9", "1:1", "Custom"],
|
| 236 |
+
value="9:16",
|
| 237 |
+
scale=2
|
| 238 |
+
)
|
| 239 |
+
|
| 240 |
+
alignment_dropdown = gr.Dropdown(
|
| 241 |
+
choices=["Middle", "Left", "Right", "Top", "Bottom"],
|
| 242 |
+
value="Middle",
|
| 243 |
+
label="Alignment"
|
| 244 |
+
)
|
| 245 |
+
|
| 246 |
+
with gr.Accordion(label="Advanced settings", open=False) as settings_panel:
|
| 247 |
+
with gr.Column():
|
| 248 |
+
with gr.Row():
|
| 249 |
+
width_slider = gr.Slider(
|
| 250 |
+
label="Target Width",
|
| 251 |
+
minimum=720,
|
| 252 |
+
maximum=1536,
|
| 253 |
+
step=8,
|
| 254 |
+
value=720,
|
| 255 |
+
)
|
| 256 |
+
height_slider = gr.Slider(
|
| 257 |
+
label="Target Height",
|
| 258 |
+
minimum=720,
|
| 259 |
+
maximum=1536,
|
| 260 |
+
step=8,
|
| 261 |
+
value=1280,
|
| 262 |
+
)
|
| 263 |
+
|
| 264 |
+
num_inference_steps = gr.Slider(label="Steps", minimum=4, maximum=12, step=1, value=8)
|
| 265 |
+
with gr.Group():
|
| 266 |
+
overlap_percentage = gr.Slider(
|
| 267 |
+
label="Mask overlap (%)",
|
| 268 |
+
minimum=1,
|
| 269 |
+
maximum=50,
|
| 270 |
+
value=10,
|
| 271 |
+
step=1
|
| 272 |
+
)
|
| 273 |
+
with gr.Row():
|
| 274 |
+
overlap_top = gr.Checkbox(label="Overlap Top", value=True)
|
| 275 |
+
overlap_right = gr.Checkbox(label="Overlap Right", value=True)
|
| 276 |
+
with gr.Row():
|
| 277 |
+
overlap_left = gr.Checkbox(label="Overlap Left", value=True)
|
| 278 |
+
overlap_bottom = gr.Checkbox(label="Overlap Bottom", value=True)
|
| 279 |
+
with gr.Row():
|
| 280 |
+
resize_option = gr.Radio(
|
| 281 |
+
label="Resize input image",
|
| 282 |
+
choices=["Full", "50%", "33%", "25%", "Custom"],
|
| 283 |
+
value="Full"
|
| 284 |
+
)
|
| 285 |
+
custom_resize_percentage = gr.Slider(
|
| 286 |
+
label="Custom resize (%)",
|
| 287 |
+
minimum=1,
|
| 288 |
+
maximum=100,
|
| 289 |
+
step=1,
|
| 290 |
+
value=50,
|
| 291 |
+
visible=False
|
| 292 |
+
)
|
| 293 |
+
|
| 294 |
+
with gr.Column():
|
| 295 |
+
preview_button = gr.Button("Preview alignment and mask")
|
| 296 |
+
|
| 297 |
+
with gr.Column():
|
| 298 |
+
result = gr.Image(
|
| 299 |
+
interactive=False,
|
| 300 |
+
label="Generated Image",
|
| 301 |
+
)
|
| 302 |
+
use_as_input_button = gr.Button("Use as Input Image", visible=False)
|
| 303 |
+
|
| 304 |
+
history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain", interactive=False)
|
| 305 |
+
preview_image = gr.Image(label="Preview")
|
| 306 |
+
|
| 307 |
+
def use_output_as_input(output_image):
|
| 308 |
+
return gr.update(value=output_image[1])
|
| 309 |
+
|
| 310 |
+
use_as_input_button.click(
|
| 311 |
+
fn=use_output_as_input,
|
| 312 |
+
inputs=[result],
|
| 313 |
+
outputs=[input_image]
|
| 314 |
+
)
|
| 315 |
+
|
| 316 |
+
target_ratio.change(
|
| 317 |
+
fn=preload_presets,
|
| 318 |
+
inputs=[target_ratio, width_slider, height_slider],
|
| 319 |
+
outputs=[width_slider, height_slider, settings_panel],
|
| 320 |
+
queue=False
|
| 321 |
+
)
|
| 322 |
+
|
| 323 |
+
width_slider.change(
|
| 324 |
+
fn=select_the_right_preset,
|
| 325 |
+
inputs=[width_slider, height_slider],
|
| 326 |
+
outputs=[target_ratio],
|
| 327 |
+
queue=False
|
| 328 |
+
)
|
| 329 |
+
|
| 330 |
+
height_slider.change(
|
| 331 |
+
fn=select_the_right_preset,
|
| 332 |
+
inputs=[width_slider, height_slider],
|
| 333 |
+
outputs=[target_ratio],
|
| 334 |
+
queue=False
|
| 335 |
+
)
|
| 336 |
+
|
| 337 |
+
resize_option.change(
|
| 338 |
+
fn=toggle_custom_resize_slider,
|
| 339 |
+
inputs=[resize_option],
|
| 340 |
+
outputs=[custom_resize_percentage],
|
| 341 |
+
queue=False
|
| 342 |
+
)
|
| 343 |
|
| 344 |
run_button.click(
|
| 345 |
+
fn=clear_result,
|
| 346 |
+
inputs=None,
|
| 347 |
+
outputs=result,
|
| 348 |
+
).then(
|
| 349 |
fn=inpaint,
|
| 350 |
+
inputs=[input_image, width_slider, height_slider, overlap_percentage, num_inference_steps,
|
| 351 |
+
resize_option, custom_resize_percentage, prompt_input, alignment_dropdown,
|
| 352 |
+
overlap_left, overlap_right, overlap_top, overlap_bottom],
|
| 353 |
+
outputs=result,
|
| 354 |
+
).then(
|
| 355 |
+
fn=lambda x, history: update_history(x[1], history),
|
| 356 |
+
inputs=[result, history_gallery],
|
| 357 |
+
outputs=history_gallery,
|
| 358 |
+
).then(
|
| 359 |
+
fn=lambda: gr.update(visible=True),
|
| 360 |
+
inputs=None,
|
| 361 |
+
outputs=use_as_input_button,
|
| 362 |
+
)
|
| 363 |
+
|
| 364 |
+
prompt_input.submit(
|
| 365 |
+
fn=clear_result,
|
| 366 |
+
inputs=None,
|
| 367 |
+
outputs=result,
|
| 368 |
+
).then(
|
| 369 |
+
fn=inpaint,
|
| 370 |
+
inputs=[input_image, width_slider, height_slider, overlap_percentage, num_inference_steps, resize_option, custom_resize_percentage, prompt_input, alignment_dropdown,
|
| 371 |
+
overlap_left, overlap_right, overlap_top, overlap_bottom],
|
| 372 |
+
outputs=result,
|
| 373 |
+
).then(
|
| 374 |
+
fn=lambda x, history: update_history(x[1], history),
|
| 375 |
+
inputs=[result, history_gallery],
|
| 376 |
+
outputs=history_gallery,
|
| 377 |
+
).then(
|
| 378 |
+
fn=lambda: gr.update(visible=True),
|
| 379 |
+
inputs=None,
|
| 380 |
+
outputs=use_as_input_button,
|
| 381 |
+
)
|
| 382 |
+
|
| 383 |
+
preview_button.click(
|
| 384 |
+
fn=preview_image_and_mask,
|
| 385 |
+
inputs=[input_image, width_slider, height_slider, overlap_percentage, resize_option, custom_resize_percentage, alignment_dropdown,
|
| 386 |
+
overlap_left, overlap_right, overlap_top, overlap_bottom],
|
| 387 |
+
outputs=preview_image,
|
| 388 |
+
queue=False
|
| 389 |
)
|
| 390 |
|
| 391 |
+
demo.queue(max_size=12).launch(share=False)
|