Spaces:
Running
on
Zero
Running
on
Zero
add condition
Browse files- app.py +1 -1
- flux1_inpaint.py +4 -3
app.py
CHANGED
@@ -61,7 +61,7 @@ with demo_blocks as demo:
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gr.HTML(read_file("demo_header.html"))
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with gr.Row():
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with gr.Column():
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image = gr.ImageEditor(height=1000,sources=['upload','clipboard'],transforms=[],image_mode='RGB', layers=False, elem_id="image_upload", type="pil", label="Upload",brush=gr.Brush(colors=["#
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with gr.Row(elem_id="prompt-container", equal_height=False):
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with gr.Row():
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prompt = gr.Textbox(label="Prompt",value="a eyes closed girl,shut eyes",placeholder="Your prompt (what you want in place of what is erased)", elem_id="prompt")
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gr.HTML(read_file("demo_header.html"))
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with gr.Row():
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with gr.Column():
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+
image = gr.ImageEditor(height=1000,sources=['upload','clipboard'],transforms=[],image_mode='RGB', layers=False, elem_id="image_upload", type="pil", label="Upload",brush=gr.Brush(colors=["#fff"], color_mode="fixed"))
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with gr.Row(elem_id="prompt-container", equal_height=False):
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with gr.Row():
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prompt = gr.Textbox(label="Prompt",value="a eyes closed girl,shut eyes",placeholder="Your prompt (what you want in place of what is erased)", elem_id="prompt")
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flux1_inpaint.py
CHANGED
@@ -36,12 +36,13 @@ def make_inpaint_condition(image, image_mask):
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def process_image(image,mask_image,prompt="a girl",negative_prompt="",model_id="black-forest-labs/FLUX.1-schnell",strength=0.75,seed=0,num_inference_steps=4):
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#control_image=make_inpaint_condition(image,mask_image)
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#image.save("_control.jpg")
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if image == None:
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return None
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pipe = FluxInpaintPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
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pipe.to(device)
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#batch_size =1
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def process_image(image,mask_image,prompt="a girl",negative_prompt="",model_id="black-forest-labs/FLUX.1-schnell",strength=0.75,seed=0,num_inference_steps=4):
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if image == None:
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return None
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+
control_image=make_inpaint_condition(image,mask_image)
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#image.save("_control.jpg")
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image = control_image
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+
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pipe = FluxInpaintPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
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pipe.to(device)
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#batch_size =1
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