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Runtime error
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7c6ef59
1
Parent(s):
a771b6a
add ref image
Browse files
app.py
CHANGED
@@ -11,19 +11,30 @@ device="cuda"
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model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1"
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pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id).to(device)
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pipe_img2img = StableDiffusionImg2ImgPipeline(**pipe_text2img.components)
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pipe_inpaint = StableDiffusionInpaintPipeline(**pipe_text2img.components)
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def
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return img
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image = output.images[0]
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return image
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@@ -35,20 +46,29 @@ with gr.Blocks() as demo:
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["女孩背影, 日落, 唯美插画"],
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]
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with gr.Row():
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with gr.Column(scale=2, ):
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output = gr.Image(label = '输出(output)')
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with gr.Column(scale=1, ):
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guide = gr.Slider(2, 15, value = 7, label = '文本引导强度(guidance scale)')
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steps = gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)')
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width = gr.Slider(256, 768, value = 512, step = 64, label = '宽度(width)')
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height = gr.Slider(256, 768, value = 512, step = 64, label = '高度(height)')
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prompt = gr.Textbox(label = '提示词(prompt)')
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submit_btn = gr.Button("
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ex = gr.Examples(examples, fn=infer, inputs=[prompt, guide, steps, width, height], outputs=output)
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submit_btn.click(fn = infer, inputs = [prompt, guide, steps, width, height], outputs = output)
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demo.queue(concurrency_count=10).launch()
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model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1"
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pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id).to(device)
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# pipe_inpaint = StableDiffusionInpaintPipeline.from_pretrained(model_id).to(device) # work
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# pipe_inpaint = StableDiffusionInpaintPipeline(**pipe_text2img.components) # not work
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pipe_img2img = StableDiffusionImg2ImgPipeline(**pipe_text2img.components)
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def infer_text2img(prompt, width, height):
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output = pipe_text2img(prompt, width=width, height=height, guidance_scale=7.5, num_inference_steps=20,)
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image = output.images[0]
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return image
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def infer_img2img(prompt, width, height, image_in, strength ):
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init_image = image_in.convert("RGB").resize((width, height))
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output = pipe_img2img(prompt, init_image=init_image, strength=strength, width=width, height=height, guidance_scale=7.5, num_inference_steps=20)
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image = output.images[0]
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return image
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def infer_inpaint(prompt, width, height, image_in):
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init_image = image_in["image"].convert("RGB").resize((width, height))
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mask = image_in["mask"].convert("RGB").resize((width, height))
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output = pipe_inpaint(prompt, \
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init_image=init_image, mask_image=mask, \
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width=width, height=height, \
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guidance_scale=7.5, num_inference_steps=20)
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image = output.images[0]
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return image
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["女孩背影, 日落, 唯美插画"],
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]
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with gr.Row():
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with gr.Column(scale=1, ):
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# guide = gr.Slider(2, 15, value = 7, label = '文本引导强度(guidance scale)')
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# steps = gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)')
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image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图")
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width = gr.Slider(256, 768, value = 512, step = 64, label = '宽度(width)')
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height = gr.Slider(256, 768, value = 512, step = 64, label = '高度(height)')
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strength = gr.Slider(0, 1.0, value = 0.8, step = 0.1, label = '参考图改变程度(strength)')
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prompt = gr.Textbox(label = '提示词(prompt)')
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submit_btn = gr.Button("生成图像(Generate)")
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with gr.Column(scale=1, ):
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image_out = gr.Image(label = '输出(output)')
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ex = gr.Examples(examples, fn=infer_text2img, inputs=[prompt, width, height], outputs=image_out)
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# with gr.Column(scale=1, ):
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# image_in = gr.Image(source='upload', tool='sketch', elem_id="image_upload", type="pil", label="Upload")
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# inpaint_prompt = gr.Textbox(label = '提示词(prompt)')
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# inpaint_btn = gr.Button("图像编辑(Inpaint)")
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# img2img_prompt = gr.Textbox(label = '提示词(prompt)')
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# img2img_btn = gr.Button("图像编辑(Inpaint)")
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if isinstance(image_in, Image.Image):
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submit_btn.click(fn = infer_img2img, inputs = [prompt, width, height, image_in, strength], outputs = image_out)
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else:
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submit_btn.click(fn = infer_text2img, inputs = [prompt, width, height], outputs = image_out)
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# inpaint_btn.click(fn = infer_inpaint, inputs = [inpaint_prompt, width, height, image_in], outputs = image_out)
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# img2img_btn.click(fn = infer_img2img, inputs = [img2img_prompt, width, height, image_in], outputs = image_out)
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demo.queue(concurrency_count=10).launch()
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