Spaces:
Building
on
A10G
Building
on
A10G
Update app.py
Browse files
app.py
CHANGED
@@ -39,7 +39,7 @@ stable_negative_prompt_list = [
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app = gr.Blocks()
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with app:
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gr.Markdown("# **<h2 align='center'>Stable Diffusion
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gr.Markdown(
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"""
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<h5 style='text-align: center'>
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@@ -196,8 +196,8 @@ with app:
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controlnet_image_file = gr.Image(label='Image')
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controlnet_model_id = gr.Dropdown(
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choices=
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value=
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label='Stable Model Id'
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)
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@@ -520,12 +520,12 @@ with app:
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controlnet_canny_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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@@ -533,72 +533,77 @@ with app:
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controlnet_hed_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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controlnet_mlsd_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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controlnet_seg_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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controlnet_depth_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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controlnet_scribble_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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controlnet_pose_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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],
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outputs = [output_image],
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)
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]
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app = gr.Blocks()
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with app:
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gr.Markdown("# **<h2 align='center'>Stable Diffusion WebUI<h2>**")
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gr.Markdown(
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"""
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<h5 style='text-align: center'>
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controlnet_image_file = gr.Image(label='Image')
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controlnet_model_id = gr.Dropdown(
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choices=stable_model_list,
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value=stable_model_list[0],
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label='Stable Model Id'
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)
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controlnet_canny_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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controlnet_hed_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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+
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controlnet_mlsd_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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controlnet_seg_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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+
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controlnet_depth_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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+
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controlnet_scribble_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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controlnet_pose_predict.click(
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fn = stable_diffusion_controlnet_img2img,
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inputs = [
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controlnet_image_file,
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controlnet_model_id,
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controlnet_prompt,
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controlnet_negative_prompt,
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controlnet_guidance_scale,
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controlnet_num_inference_step,
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],
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outputs = [output_image],
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)
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