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Runtime error
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305f206
1
Parent(s):
aab1f68
Image Download (#4)
Browse files- Image Download (3c63bff61c6dd2f21051412cb98945e6af074801)
Co-authored-by: Morpheus <6Morpheus6@users.noreply.huggingface.co>
app.py
CHANGED
@@ -69,9 +69,10 @@ pipe = StableDiffusionXLInstantIDPipeline.from_pretrained(
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feature_extractor=None,
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)
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#pipe.cuda()
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-
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-
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-
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# LCM
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if os.environ.get("MODE") == "LCM":
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@@ -311,13 +312,18 @@ def generate_image(
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generator=generator,
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).images
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gc.collect()
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if device == 'mps':
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torch.mps.empty_cache()
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elif device == 'cuda':
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torch.cuda.empty_cache()
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return images[0], gr.update(visible=True)
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### Description
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@@ -363,8 +369,10 @@ tips = r"""
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"""
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css = """
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.gradio-container {width:
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"""
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with gr.Blocks(css=css) as demo:
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# description
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gr.Markdown(title)
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@@ -392,7 +400,7 @@ with gr.Blocks(css=css) as demo:
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# strength
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identitynet_strength_ratio = gr.Slider(
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label="IdentityNet strength (for
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minimum=0,
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maximum=1.5,
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step=0.05,
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@@ -410,7 +418,7 @@ with gr.Blocks(css=css) as demo:
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negative_prompt = gr.Textbox(
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label="Negative Prompt",
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placeholder="low quality",
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value="(lowres, low quality, worst quality:1.2), (text:1.2),
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)
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num_steps = gr.Slider(
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label="Number of sample steps",
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@@ -438,6 +446,7 @@ with gr.Blocks(css=css) as demo:
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips, visible=False)
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submit.click(
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@@ -471,13 +480,13 @@ with gr.Blocks(css=css) as demo:
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guidance_scale,
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seed,
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],
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outputs=[output_image, usage_tips],
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)
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gr.Examples(
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examples=get_example(),
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inputs=[face_file, prompt, style, negative_prompt],
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outputs=[output_image, usage_tips],
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fn=run_for_examples,
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)
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feature_extractor=None,
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)
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#pipe.cuda()
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if os.environ.get("MODE") == "Default":
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print("Default")
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num_inference_steps = 30
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guidance_scale = 5
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# LCM
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if os.environ.get("MODE") == "LCM":
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generator=generator,
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).images
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gradio_temp_dir = os.environ['GRADIO_TEMP_DIR']
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temp_file_path = os.path.join(gradio_temp_dir, "image.png")
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images[0].save(temp_file_path, format="PNG")
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print(f"Image saved in: {temp_file_path}")
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gc.collect()
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if device == 'mps':
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torch.mps.empty_cache()
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elif device == 'cuda':
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torch.cuda.empty_cache()
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return images[0], gr.update(visible=True), temp_file_path
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### Description
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"""
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css = """
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.gradio-container { width: 90% !important }
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#row-height { height: 65px !important }
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"""
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with gr.Blocks(css=css) as demo:
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# description
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gr.Markdown(title)
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# strength
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identitynet_strength_ratio = gr.Slider(
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label="IdentityNet strength (for fidelity)",
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minimum=0,
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maximum=1.5,
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step=0.05,
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negative_prompt = gr.Textbox(
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label="Negative Prompt",
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placeholder="low quality",
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value="(lowres, low quality, worst quality:1.2), (text:1.2), (frame:1.2), watermark, deformed, ugly, deformed eyes, blur, blurry, noisy, out of focus, nudity, naked, skimpy, scanty, bare skin, exposed, monochrome, pet collar",
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)
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num_steps = gr.Slider(
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label="Number of sample steps",
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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download_image = gr.File(label="Download Image", file_count="single", elem_id="row-height")
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usage_tips = gr.Markdown(label="Usage tips of InstantID", value=tips, visible=False)
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submit.click(
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guidance_scale,
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seed,
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],
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outputs=[output_image, usage_tips, download_image],
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)
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gr.Examples(
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examples=get_example(),
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inputs=[face_file, prompt, style, negative_prompt],
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outputs=[output_image, usage_tips, download_image],
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fn=run_for_examples,
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)
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