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Update app.py
Browse filesadded delete background
app.py
CHANGED
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@@ -5,6 +5,9 @@ import random
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# import spaces #[uncomment to use ZeroGPU]
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from diffusers import DiffusionPipeline
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from peft import PeftModel, PeftConfig
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import torch
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from typing import Optional
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@@ -94,6 +97,7 @@ def infer(
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num_inference_steps: int = 20,
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scheduler_name: Optional[str] = None,
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lora_scale: float = 1.0,
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progress=gr.Progress(track_tqdm=True),
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):
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# получаем/загружаем нужный pipe
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@@ -132,6 +136,18 @@ def infer(
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generator=generator,
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).images[0]
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return image, seed
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@@ -174,7 +190,7 @@ with gr.Blocks(css=css) as demo:
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minimum=0.0,
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maximum=3.0,
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step=0.1,
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value=
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visible=False, # Initially hidden
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)
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@@ -192,6 +208,12 @@ with gr.Blocks(css=css) as demo:
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result = gr.Image(label="Result", show_label=False)
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with gr.Accordion("Advanced Settings", open=False):
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negative_prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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@@ -272,7 +294,8 @@ with gr.Blocks(css=css) as demo:
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guidance_scale,
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num_inference_steps,
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scheduler_select,
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lora_scale_slider
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],
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outputs=[result, seed],
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)
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# import spaces #[uncomment to use ZeroGPU]
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from diffusers import DiffusionPipeline
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from peft import PeftModel, PeftConfig
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from rembg import remove
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from PIL import Image
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import io
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import torch
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from typing import Optional
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num_inference_steps: int = 20,
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scheduler_name: Optional[str] = None,
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lora_scale: float = 1.0,
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remove_background: bool = False,
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progress=gr.Progress(track_tqdm=True),
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):
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# получаем/загружаем нужный pipe
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generator=generator,
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).images[0]
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if remove_background:
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# Конвертируем PIL Image в bytes
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img_byte_arr = io.BytesIO()
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image.save(img_byte_arr, format='PNG')
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img_byte_arr = img_byte_arr.getvalue()
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# Удаляем фон
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output_image = remove(img_byte_arr)
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# Конвертируем обратно в PIL Image
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image = Image.open(io.BytesIO(output_image))
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return image, seed
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minimum=0.0,
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maximum=3.0,
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step=0.1,
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value=1.8,
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visible=False, # Initially hidden
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)
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result = gr.Image(label="Result", show_label=False)
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with gr.Accordion("Advanced Settings", open=False):
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remove_background = gr.Checkbox(
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label="Remove background from generated image",
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value=False,
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info="Use rembg to remove background from the generated image"
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)
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negative_prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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guidance_scale,
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num_inference_steps,
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scheduler_select,
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lora_scale_slider,
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remove_background
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],
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outputs=[result, seed],
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)
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