Dhruv Diddi
commited on
Commit
·
af48b88
1
Parent(s):
a2a4738
update docs
Browse files
app.py
CHANGED
@@ -6,6 +6,9 @@ import json
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import os
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import random
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import tempfile
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import gradio as gr
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import torch
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@@ -105,15 +108,18 @@ def upload_stage1_result(stage1_param_path: str, stage1_result_path: str,
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if not UPLOAD_REPO_ID:
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return
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try:
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except Exception as e:
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print(e)
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@@ -140,18 +146,20 @@ def upload_stage2_info(stage1_param_file_hash_name: str,
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param_file.write(json.dumps(stage2_params))
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stage2_param_file_hash_name = get_param_file_hash_name(param_file.name)
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save_name = f'{stage1_param_file_hash_name}_{stage2_param_file_hash_name}'
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try:
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if UPLOAD_RESULT_IMAGE:
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except Exception as e:
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print(e)
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@@ -188,17 +196,16 @@ def upload_stage2_3_info(stage1_param_file_hash_name: str,
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save_name = f'{stage1_param_file_hash_name}_{stage2_3_param_file_hash_name}'
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try:
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if UPLOAD_RESULT_IMAGE:
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repo_type='dataset')
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except Exception as e:
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print(e)
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@@ -221,6 +228,22 @@ def show_gallery_view() -> tuple[dict, dict]:
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def show_upscaled_view() -> tuple[dict, dict]:
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return _update_result_view(False)
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examples = [
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'high quality dslr photo, a photo product of a lemon inspired by natural and organic materials, wooden accents, intricately decorated with glowing vines of led lights, inspired by baroque luxury',
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@@ -239,6 +262,8 @@ examples = [
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]
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with gr.Blocks(css='style.css') as demo:
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with gr.Box():
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with gr.Row(elem_id='prompt-container').style(equal_height=True):
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with gr.Column():
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@@ -249,6 +274,13 @@ with gr.Blocks(css='style.css') as demo:
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placeholder='Enter your prompt',
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elem_id='prompt-text-input',
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).style(container=False)
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generate_button = gr.Button('Generate').style(full_width=False)
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with gr.Column() as gallery_view:
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@@ -274,7 +306,12 @@ with gr.Blocks(css='style.css') as demo:
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interactive=False,
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elem_id='upscaled-image').style(height=640)
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back_to_selection_button = gr.Button('Back to selection')
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-
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with gr.Accordion('Advanced options',
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open=False,
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visible=SHOW_ADVANCED_OPTIONS):
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@@ -385,12 +422,12 @@ with gr.Blocks(css='style.css') as demo:
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gr.HTML(FOOTER)
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stage1_inputs = [
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prompt,
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]
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stage1_outputs = [
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gallery,
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@@ -441,6 +478,49 @@ with gr.Blocks(css='style.css') as demo:
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queue=False,
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)
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generate_button.click(
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fn=randomize_seed_fn,
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inputs=[seed_1, randomize_seed_1],
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@@ -553,7 +633,7 @@ with gr.Blocks(css='style.css') as demo:
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custom_timesteps_2,
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num_inference_steps_2,
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prompt,
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-
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seed_3,
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guidance_scale_3,
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num_inference_steps_3,
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@@ -596,7 +676,7 @@ with gr.Blocks(css='style.css') as demo:
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custom_timesteps_2,
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num_inference_steps_2,
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prompt,
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seed_3,
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guidance_scale_3,
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num_inference_steps_3,
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@@ -612,5 +692,10 @@ with gr.Blocks(css='style.css') as demo:
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],
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queue=False,
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)
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demo.queue(api_open=
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import os
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import random
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import tempfile
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import shortuuid
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from apscheduler.schedulers.background import BackgroundScheduler
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import shutil
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import gradio as gr
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import torch
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if not UPLOAD_REPO_ID:
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return
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try:
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folder_params = "tmp/results/stage1_params"
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folder_results = "tmp/results/stage1_results"
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path_params = f"{folder_params}/{save_name}.json"
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path_results = f"{folder_results}/{save_name}.pth"
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os.makedirs(folder_params, exist_ok=True)
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os.makedirs(folder_results, exist_ok=True)
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shutil.copy(stage1_param_path, path_params)
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shutil.copy(stage1_result_path, path_results)
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except Exception as e:
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print(e)
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param_file.write(json.dumps(stage2_params))
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stage2_param_file_hash_name = get_param_file_hash_name(param_file.name)
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save_name = f'{stage1_param_file_hash_name}_{stage2_param_file_hash_name}'
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try:
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folder_params = "tmp/results/stage2_params"
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os.makedirs(folder_params, exist_ok=True)
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path_params = f"{folder_params}/{save_name}.json"
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shutil.copy(param_file.name, path_params)
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if UPLOAD_RESULT_IMAGE:
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folder_results = "tmp/results/stage2_results"
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os.makedirs(folder_results, exist_ok=True)
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path_results = f"{folder_results}/{save_name}.png"
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shutil.copy(stage2_output_path, path_results)
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except Exception as e:
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print(e)
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save_name = f'{stage1_param_file_hash_name}_{stage2_3_param_file_hash_name}'
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try:
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folder_params = "tmp/results/stage2_3_params"
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os.makedirs(folder_params, exist_ok=True)
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path_params = f"{folder_params}/{save_name}.json"
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shutil.copy(param_file.name, path_params)
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if UPLOAD_RESULT_IMAGE:
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folder_results = "tmp/results/stage2_3_results"
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os.makedirs(folder_results, exist_ok=True)
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path_results = f"{folder_results}/{save_name}.png"
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shutil.copy(stage2_3_output_path, path_results)
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except Exception as e:
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print(e)
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def show_upscaled_view() -> tuple[dict, dict]:
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return _update_result_view(False)
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def upload_files():
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"""Zips files and uploads to dataset. Local data is deleted
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"""
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if os.path.exists("tmp/results") and os.path.isdir("tmp/results"):
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try:
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random_folder = random.randint(0,1000)
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shutil.make_archive("tmp/results", 'zip', "tmp/results")
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hf_api.upload_file(
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path_or_fileobj="tmp/results.zip",
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path_in_repo=f"{random_folder}/results_{shortuuid.uuid()}.zip",
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repo_id=UPLOAD_REPO_ID,
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repo_type="dataset",
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)
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shutil.rmtree("tmp/results")
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except Exception as e:
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print(e)
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examples = [
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'high quality dslr photo, a photo product of a lemon inspired by natural and organic materials, wooden accents, intricately decorated with glowing vines of led lights, inspired by baroque luxury',
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]
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with gr.Blocks(css='style.css') as demo:
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gr.Markdown(TITLE)
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gr.Markdown(DESCRIPTION)
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with gr.Box():
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with gr.Row(elem_id='prompt-container').style(equal_height=True):
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with gr.Column():
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placeholder='Enter your prompt',
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elem_id='prompt-text-input',
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).style(container=False)
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negative_prompt = gr.Text(
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label='Negative prompt',
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show_label=False,
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max_lines=1,
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placeholder='Enter a negative prompt',
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elem_id='negative-prompt-text-input',
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).style(container=False)
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generate_button = gr.Button('Generate').style(full_width=False)
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with gr.Column() as gallery_view:
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interactive=False,
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elem_id='upscaled-image').style(height=640)
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back_to_selection_button = gr.Button('Back to selection')
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with gr.Group(elem_id="share-btn-container"):
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community_icon = gr.HTML(community_icon_html)
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loading_icon = gr.HTML(loading_icon_html)
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share_button = gr.Button(
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"Share to community", elem_id="share-btn")
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share_button.click(None, [], [], _js=share_js)
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with gr.Accordion('Advanced options',
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open=False,
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visible=SHOW_ADVANCED_OPTIONS):
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gr.HTML(FOOTER)
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stage1_inputs = [
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prompt,
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negative_prompt,
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seed_1,
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num_images,
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guidance_scale_1,
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custom_timesteps_1,
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num_inference_steps_1,
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]
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stage1_outputs = [
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gallery,
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queue=False,
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)
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negative_prompt.submit(
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fn=randomize_seed_fn,
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inputs=[seed_1, randomize_seed_1],
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outputs=seed_1,
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queue=False,
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).then(
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fn=lambda: -1,
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outputs=selected_index_for_stage2,
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queue=False,
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).then(
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fn=show_gallery_view,
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outputs=[
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gallery_view,
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upscale_view,
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],
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queue=False,
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).then(
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fn=update_upscale_button,
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inputs=selected_index_for_stage2,
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outputs=[
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upscale_button,
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upscale_to_256_button,
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],
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queue=False,
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).then(
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fn=model.run_stage1,
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inputs=stage1_inputs,
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outputs=stage1_outputs,
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).success(
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fn=get_param_file_hash_name,
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inputs=stage1_param_path,
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outputs=stage1_param_file_hash_name,
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queue=False,
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).then(
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fn=upload_stage1_result,
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inputs=[
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stage1_param_path,
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stage1_result_path,
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stage1_param_file_hash_name,
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],
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queue=False,
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)
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generate_button.click(
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fn=randomize_seed_fn,
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inputs=[seed_1, randomize_seed_1],
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custom_timesteps_2,
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num_inference_steps_2,
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prompt,
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negative_prompt,
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seed_3,
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guidance_scale_3,
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num_inference_steps_3,
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custom_timesteps_2,
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num_inference_steps_2,
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prompt,
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negative_prompt,
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seed_3,
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guidance_scale_3,
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num_inference_steps_3,
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],
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queue=False,
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)
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if UPLOAD_REPO_ID:
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scheduler = BackgroundScheduler()
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scheduler.add_job(func=upload_files, trigger="interval", seconds=60*20)
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scheduler.start()
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demo.queue(api_open=False, max_size=MAX_QUEUE_SIZE).launch(debug=DEBUG)
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