allknowingroger
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Duplicate from allknowingroger/Image-Models-Test82
Browse files- .gitattributes +34 -0
- README.md +13 -0
- app.py +145 -0
.gitattributes
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README.md
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---
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title: More Image Models
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emoji: 😻
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colorFrom: red
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colorTo: gray
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sdk: gradio
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sdk_version: 3.23.0
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app_file: app.py
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pinned: true
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duplicated_from: allknowingroger/Image-Models-Test82
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---
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<!--Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference-->
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app.py
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import gradio as gr
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# import os
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# import sys
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# from pathlib import Path
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import time
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models =[
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"camus-ng/lora-trained-xl",
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"melt200x/test2",
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"stephanebhiri/lora-trained-xl-colab-stp21",
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"ATmeraki/lora-trained-xl-colab",
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"stephanebhiri/lora-trained-xl-colab-stp20",
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"wavymulder/portraitplus",
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"wavymulder/wavyfusion",
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"ItsJayQz/GTA5_Artwork_Diffusion",
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"ItsJayQz/SynthwavePunk-v2",
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"Yntec/MapleSyrup",
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]
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model_functions = {}
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model_idx = 1
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for model_path in models:
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try:
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model_functions[model_idx] = gr.Interface.load(f"models/{model_path}", live=False, preprocess=True, postprocess=False)
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except Exception as error:
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def the_fn(txt):
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return None
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model_functions[model_idx] = gr.Interface(fn=the_fn, inputs=["text"], outputs=["image"])
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model_idx+=1
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def send_it_idx(idx):
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def send_it_fn(prompt):
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output = (model_functions.get(str(idx)) or model_functions.get(str(1)))(prompt)
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return output
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return send_it_fn
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def get_prompts(prompt_text):
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return prompt_text
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def clear_it(val):
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if int(val) != 0:
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val = 0
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else:
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val = 0
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pass
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return val
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def all_task_end(cnt,t_stamp):
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to = t_stamp + 60
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et = time.time()
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if et > to and t_stamp != 0:
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d = gr.update(value=0)
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tog = gr.update(value=1)
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#print(f'to: {to} et: {et}')
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else:
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if cnt != 0:
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d = gr.update(value=et)
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else:
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d = gr.update(value=0)
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tog = gr.update(value=0)
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#print (f'passing: to: {to} et: {et}')
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pass
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return d, tog
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def all_task_start():
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print("\n\n\n\n\n\n\n")
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t = time.gmtime()
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t_stamp = time.time()
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current_time = time.strftime("%H:%M:%S", t)
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return gr.update(value=t_stamp), gr.update(value=t_stamp), gr.update(value=0)
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def clear_fn():
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nn = len(models)
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return tuple([None, *[None for _ in range(nn)]])
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with gr.Blocks(title="SD Models") as my_interface:
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with gr.Column(scale=12):
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# with gr.Row():
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# gr.Markdown("""- Primary prompt: 你想画的内容(英文单词,如 a cat, 加英文逗号效果更好;点 Improve 按钮进行完善)\n- Real prompt: 完善后的提示词,出现后再点右边的 Run 按钮开始运行""")
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with gr.Row():
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with gr.Row(scale=6):
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primary_prompt=gr.Textbox(label="Prompt", value="")
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# real_prompt=gr.Textbox(label="Real prompt")
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with gr.Row(scale=6):
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# improve_prompts_btn=gr.Button("Improve")
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with gr.Row():
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run=gr.Button("Run",variant="primary")
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clear_btn=gr.Button("Clear")
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with gr.Row():
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sd_outputs = {}
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model_idx = 1
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for model_path in models:
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with gr.Column(scale=3, min_width=320):
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with gr.Box():
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sd_outputs[model_idx] = gr.Image(label=model_path)
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pass
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model_idx += 1
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pass
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pass
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with gr.Row(visible=False):
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start_box=gr.Number(interactive=False)
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end_box=gr.Number(interactive=False)
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tog_box=gr.Textbox(value=0,interactive=False)
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start_box.change(
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all_task_end,
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[start_box, end_box],
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[start_box, tog_box],
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every=1,
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show_progress=False)
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primary_prompt.submit(all_task_start, None, [start_box, end_box, tog_box])
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run.click(all_task_start, None, [start_box, end_box, tog_box])
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runs_dict = {}
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model_idx = 1
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for model_path in models:
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runs_dict[model_idx] = run.click(model_functions[model_idx], inputs=[primary_prompt], outputs=[sd_outputs[model_idx]])
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model_idx += 1
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pass
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pass
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# improve_prompts_btn_clicked=improve_prompts_btn.click(
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# get_prompts,
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# inputs=[primary_prompt],
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# outputs=[primary_prompt],
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# cancels=list(runs_dict.values()))
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clear_btn.click(
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clear_fn,
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None,
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[primary_prompt, *list(sd_outputs.values())],
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cancels=[*list(runs_dict.values())])
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tog_box.change(
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clear_it,
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tog_box,
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tog_box,
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cancels=[*list(runs_dict.values())])
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my_interface.queue(concurrency_count=600, status_update_rate=1)
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my_interface.launch(inline=True, show_api=False)
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