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2905c29
Create app.py
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app.py
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import gradio as gr
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from time import sleep
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from diffusers import DiffusionPipeline
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import torch
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import json
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import random
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lora_list = hf_hub_download(repo_id="multimodalart/LoraTheExplorer", filename="sdxl_loras.json", repo_type="space")
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with open(lora_list, "r") as file:
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data = json.load(file)
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sdxl_loras = [
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{
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"image": item["image"],
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"title": item["title"],
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"repo": item["repo"],
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"trigger_word": item["trigger_word"],
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"weights": item["weights"],
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"is_compatible": item["is_compatible"],
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"is_pivotal": item.get("is_pivotal", False),
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"text_embedding_weights": item.get("text_embedding_weights", None),
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"is_nc": item.get("is_nc", False)
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}
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for item in data
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]
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saved_names = [
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hf_hub_download(item["repo"], item["weights"]) for item in sdxl_loras
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]
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css = '''
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#title{text-align:center}
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#plus_column{align-self: center}
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#plus_button{font-size: 250%; text-align: center}
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.gradio-container{width: 700px !important; margin: 0 auto !important}
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#prompt input{width: calc(100% - 160px);border-top-right-radius: 0px;border-bottom-right-radius: 0px;}
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#run_button{position:absolute;margin-top: 57px;right: 0;margin-right: 0.8em;border-bottom-left-radius: 0px;
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border-top-left-radius: 0px;}
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'''
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pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
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original_pipe = copy.deepcopy(pipe)
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def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
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pipe = copy.deepcopy(original_pipe)
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pipe.load_lora_weights(shuffled_items[0]['repo'], weight_name=shuffled_items[0]['weights'])
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pipe.fuse_lora(lora_1_scale)
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pipe.load_lora_weights(shuffled_items[1]['repo'], weight_name=shuffled_items[1]['weights'])
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pipe.fuse_lora(lora_2_scale)
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pipe.to(torch_dtype=torch.float16)
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pipe.to("cuda")
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if negative_prompt == "":
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negative_prompt = False
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image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=25, guidance_scale=7).images[0]
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return image
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def get_description(item):
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trigger_word = item["trigger_word"]
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return f"LoRA trigger word: `{trigger_word}`" if trigger_word else "LoRA trigger word: `none`, will be applied automatically", trigger_word
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def shuffle_images():
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compatible_items = [item for item in data if item['is_compatible']]
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random.shuffle(compatible_items)
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two_shuffled_items = compatible_items[:2]
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title_1 = gr.update(label=two_shuffled_items[0]['title'], value=two_shuffled_items[0]['image'])
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title_2 = gr.update(label=two_shuffled_items[1]['title'], value=two_shuffled_items[1]['image'])
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description_1, trigger_word_1 = get_description(two_shuffled_items[0])
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description_2, trigger_word_2 = get_description(two_shuffled_items[1])
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prompt = gr.update(value=f"{trigger_word_1} {trigger_word_2}")
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return title_1,description_1,title_2,description_2,prompt, two_shuffled_items
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with gr.Blocks(css=css) as demo:
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shuffled_items = gr.State()
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title = gr.HTML(
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'''<h1>LoRA Roulette 🎲</h1>
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<h4>Two LoRAs are loaded to SDXL at random, find a way to combine them for your art 🎨</h4>
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''',
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elem_id="title"
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)
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with gr.Row():
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with gr.Column(min_width=10, scale=6):
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lora_1 = gr.Image(interactive=False, height=350)
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lora_1_prompt = gr.Markdown()
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with gr.Column(min_width=10, scale=1, elem_id="plus_column"):
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plus = gr.HTML("+", elem_id="plus_button")
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with gr.Column(min_width=10, scale=6):
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lora_2 = gr.Image(interactive=False, height=350)
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lora_2_prompt = gr.Markdown()
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with gr.Row():
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prompt = gr.Textbox(label="Your prompt", info="arrange the trigger words of the two LoRAs in a coherent sentence", interactive=True, elem_id="prompt")
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run_btn = gr.Button("Run", elem_id="run_button")
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output_image = gr.Image()
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with gr.Accordion("Advanced settings", open=False):
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negative_prompt = gr.Textbox(label="Negative prompt")
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with gr.Row():
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lora_1_scale = gr.Slider(label="LoRA 1 Scale", minimum=0, maximum=1, step=0.1, value=0.7)
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lora_2_scale = gr.Slider(label="LoRa 2 Scale", minimum=0, maximum=1, step=0.1, value=0.7)
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shuffle_button = gr.Button("Reshuffle LoRAs!")
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demo.load(shuffle_images, inputs=[], outputs=[lora_1,lora_1_prompt,lora_2,lora_2_prompt, prompt, shuffled_items], queue=False, show_progress="hidden")
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shuffle_button.click(shuffle_images, outputs=[lora_1,lora_1_prompt,lora_2,lora_2_prompt, prompt, shuffled_items], queue=False, show_progress="hidden")
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run_btn.click(merge_and_run, inputs=[prompt, negative_prompt, shuffled_items, lora_1_scale, lora_2_scale], outputs=[output_image])
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prompt.submit(merge_and_run, inputs=[prompt, negative_prompt, shuffled_items, lora_1_scale, lora_2_scale], outputs=[output_image])
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demo.queue()
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demo.launch()
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