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Starting
on
A10G
Starting
on
A10G
edit device; edit dropdown
Browse files- app.py +10 -8
- inference.py +4 -3
app.py
CHANGED
@@ -1,11 +1,11 @@
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#!/usr/bin/env python
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"""Demo app for https://github.com/ziqihuangg/ReVersion.
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The code in this repo is partly adapted from the following repository:
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https://huggingface.co/spaces/
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S-Lab License 1.0
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Copyright
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Redistribution and use for non-commercial purpose in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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@@ -101,13 +101,13 @@ def reload_custom_diffusion_weight_list() -> dict:
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return gr.update(choices=find_weight_files())
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def create_inference_demo(func: inference_fn) -> gr.Blocks:
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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model_id = gr.Dropdown(
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choices=['
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value='
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label='Relation',
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visible=True)
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# reload_button = gr.Button('Reload Weight List')
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@@ -151,7 +151,8 @@ def create_inference_demo(func: inference_fn) -> gr.Blocks:
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prompt,
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placeholder_string,
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num_samples,
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guidance_scale
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],
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outputs=result,
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queue=False)
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@@ -161,7 +162,8 @@ def create_inference_demo(func: inference_fn) -> gr.Blocks:
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prompt,
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placeholder_string,
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num_samples,
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guidance_scale
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],
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outputs=result,
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queue=False)
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@@ -184,7 +186,7 @@ with gr.Blocks(css='style.css') as demo:
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with gr.Tabs():
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with gr.TabItem('Test'):
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create_inference_demo(inference_fn)
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demo.launch(
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enable_queue=args.enable_queue,
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#!/usr/bin/env python
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"""Demo app for https://github.com/ziqihuangg/ReVersion.
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The code in this repo is partly adapted from the following repository:
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+
https://huggingface.co/spaces/nupurkmr9/custom-diffusion
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S-Lab License 1.0
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Copyright 2023 S-Lab
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Redistribution and use for non-commercial purpose in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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return gr.update(choices=find_weight_files())
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def create_inference_demo(func: inference_fn, device=args.device) -> gr.Blocks:
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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model_id = gr.Dropdown(
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choices=['painted_on'],
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value='painted_on',
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label='Relation',
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visible=True)
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# reload_button = gr.Button('Reload Weight List')
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prompt,
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placeholder_string,
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num_samples,
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guidance_scale,
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device
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],
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outputs=result,
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queue=False)
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prompt,
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placeholder_string,
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num_samples,
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guidance_scale,
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device
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],
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outputs=result,
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queue=False)
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with gr.Tabs():
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with gr.TabItem('Test'):
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create_inference_demo(inference_fn, args.device)
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demo.launch(
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enable_queue=args.enable_queue,
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inference.py
CHANGED
@@ -46,14 +46,15 @@ def inference_fn(
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prompt,
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placeholder_string,
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num_samples,
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guidance_scale
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):
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# create inference pipeline
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pipe = StableDiffusionPipeline.from_pretrained(model_id,torch_dtype=torch.float16).to(
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# make directory to save images
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image_root_folder = os.path.join(model_id, 'inference')
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os.makedirs(image_root_folder, exist_ok = True)
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# if prompt is None and args.template_name is None:
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prompt,
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placeholder_string,
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num_samples,
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guidance_scale,
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device
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):
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# create inference pipeline
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pipe = StableDiffusionPipeline.from_pretrained(model_id,torch_dtype=torch.float16).to(device)
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# make directory to save images
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image_root_folder = os.path.join('experiments', model_id, 'inference')
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os.makedirs(image_root_folder, exist_ok = True)
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# if prompt is None and args.template_name is None:
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