Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -73,7 +73,73 @@ def inpaintGen(
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).images[0]
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return result, seed
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with gr.Blocks(theme="ocean", title="Flux.1 Fill dev", css=CSS) as demo:
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gr.HTML("<h1><center>Flux.1 Fill dev</center></h1>")
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@@ -84,36 +150,77 @@ with gr.Blocks(theme="ocean", title="Flux.1 Fill dev", css=CSS) as demo:
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</center>
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</p>
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""")
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with gr.
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with gr.
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with gr.Row():
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if __name__ == "__main__":
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demo.queue(api_open=False).launch(show_api=False, share=False)
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).images[0]
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return result, seed
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@spaces.GPU():
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def outpaintGen(
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img,
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outpaint_prompt: str,
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overlay_top: int,
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overlay_right: int,
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overlay_bottom: int,
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overlay_left: int,
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op_guidance: float,
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op_num_steps: int,
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op_seed: int,
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op_randomize_seed: bool,
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progress=gr.Progress(track_tqdm=True)
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):
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image = Image.open(img)
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# Convert input to PIL Image if it's a numpy array
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if isinstance(image, np.ndarray):
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image = Image.fromarray(image)
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# Get original dimensions
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original_width, original_height = image.size
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# Calculate new dimensions
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new_width = original_width + overlap_left + overlap_right
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new_height = original_height + overlap_top + overlap_bottom
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# Create new blank mask image (black background)
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mask_image = Image.new('RGB', (new_width, new_height), color='black')
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# Create white rectangle for original image area
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white_area = Image.new('RGB', (original_width, original_height), color='white')
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# Paste white rectangle at the appropriate position
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mask_image.paste(white_area, (overlap_left, overlap_top))
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# Convert to grayscale
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mask_image = mask_image.convert('L')
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fix_width = (new_width // 16) * 16
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fix_height = (new_height // 16) * 16
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# If the image size is not already divisible by 16, resize it
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if new_width != fix_width or new_height != fix_height:
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mask_image = mask_image.resize((fix_width, fix_height), Image.LANCZOS)
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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generator = torch.Generator("cpu").manual_seed(seed)
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result = pipe(
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prompt=inpaint_prompt,
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image=image,
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mask_image=mask_image,
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width=fix_width,
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height=fix_height,
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num_inference_steps=num_steps,
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generator=generator,
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guidance_scale=guidance,
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max_sequence_length=512,
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).images[0]
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return result, seed
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with gr.Blocks(theme="ocean", title="Flux.1 Fill dev", css=CSS) as demo:
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gr.HTML("<h1><center>Flux.1 Fill dev</center></h1>")
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</center>
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</p>
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""")
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with gr.Tab("Inpainting"):
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with gr.Row():
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with gr.Column():
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imgMask = gr.ImageMask(type="filepath", label="Image", layers=False, height=800)
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inpaint_prompt = gr.Textbox(label='Prompts ✏️', placeholder="A hat...")
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with gr.Row():
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Inpaint_sendBtn = gr.Button(value="Submit", variant='primary')
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Inpaint_clearBtn = gr.ClearButton([imgMask, inpaint_prompt], value="Clear")
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image_out = gr.Image(type="pil", label="Output", height=960)
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with gr.Accordion("Advanced ⚙️", open=False):
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guidance = gr.Slider(label="Guidance scale", minimum=1, maximum=50, value=30.0, step=0.1)
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num_steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=20, step=1)
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seed = gr.Number(label="Seed", value=42, precision=0)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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gr.on(
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triggers = [
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inpaint_prompt.submit,
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Inpaint_sendBtn.click,
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],
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fn = inpaintGen,
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inputs = [
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imgMask,
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inpaint_prompt,
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guidance,
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num_steps,
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seed,
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randomize_seed
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],
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outputs = [image_out, seed]
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)
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with gr.Tab("Outpainting"):
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with gr.Row():
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with gr.Column():
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img = gr.Image(type="filepath", label="Image", height=800)
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outpaint_prompt = gr.Textbox(label='Prompts ✏️', placeholder="In city...")
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with gr.Row():
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outpaint_sendBtn = gr.Button(value="Submit", variant='primary')
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outpaint_clearBtn = gr.ClearButton([img, outpaint_prompt], value="Clear")
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image_exp = gr.Image(type="pil", label="Output", height=960)
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with gr.Accordion("Advanced ⚙️", open=False):
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with gr.Row():
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overlay_top = gr.Number(label="Top", value=60, precision=0)
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overlay_right = gr.Number(label="Right", value=60, precision=0)
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overlay_bottom = gr.Number(label="Bottom", value=60, precision=0)
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overlay_left = gr.Number(label="Left", value=60, precision=0)
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op_guidance = gr.Slider(label="Guidance scale", minimum=1, maximum=50, value=30.0, step=0.1)
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op_num_steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=20, step=1)
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op_seed = gr.Number(label="Seed", value=42, precision=0)
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op_randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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gr.on(
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triggers = [
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outpaint_prompt.submit,
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outpaint_sendBtn.click,
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],
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fn = outpaintGen,
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inputs = [
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img,
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outpaint_prompt,
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overlay_top,
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overlay_right,
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overlay_bottom,
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overlay_left,
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op_guidance,
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op_num_steps,
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op_seed,
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op_randomize_seed
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],
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outputs = [image_exp, op_seed]
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)
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if __name__ == "__main__":
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demo.queue(api_open=False).launch(show_api=False, share=False)
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