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Update app.py
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app.py
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#!/usr/bin/env python
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import os
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import random
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import uuid
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@@ -13,10 +15,7 @@ import torch
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from diffusers import DiffusionPipeline
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from typing import Tuple
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#
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bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
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bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
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default_negative = os.getenv("default_negative","")
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@@ -30,10 +29,12 @@ def check_text(prompt, negative=""):
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return True
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return False
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style_list = [
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{
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"name": "2560 x 1440",
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"prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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@@ -41,46 +42,140 @@ style_list = [
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},
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{
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"name": "
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"prompt": "
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"negative_prompt": "
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},
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{
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"name": "Cinematic",
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"prompt": "cinematic
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"negative_prompt": "
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},
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{
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"name": "
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"prompt": "
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"negative_prompt": "
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},
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{
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"name": "
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"prompt": "
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"negative_prompt": "
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},
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{
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"name": "
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"prompt": "{prompt}",
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"negative_prompt": "",
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},
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]
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styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
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STYLE_NAMES = list(styles.keys())
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-
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def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
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if not negative:
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negative = ""
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return p.replace("{prompt}", positive), n + negative
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DESCRIPTION = """## MidJourney
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"""
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if not torch.cuda.is_available():
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DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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NUM_IMAGES_PER_PROMPT = 1
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if torch.cuda.is_available():
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pipe = DiffusionPipeline.from_pretrained(
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"SG161222/
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torch_dtype=torch.float16,
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use_safetensors=True,
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add_watermarker=False,
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variant="fp16"
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)
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"SG161222/RealVisXL_V2.02_Turbo",
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torch_dtype=torch.float16,
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use_safetensors=True,
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add_watermarker=False,
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variant="fp16"
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)
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if ENABLE_CPU_OFFLOAD:
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pipe.enable_model_cpu_offload()
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pipe2.enable_model_cpu_offload()
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else:
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pipe.to(device)
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pipe2.to(device)
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print("Loaded on Device!")
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if USE_TORCH_COMPILE:
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pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
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pipe2.unet = torch.compile(pipe2.unet, mode="reduce-overhead", fullgraph=True)
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print("Model Compiled!")
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def save_image(img):
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img.save(unique_name)
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return unique_name
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def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
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if randomize_seed:
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negative_prompt: str = "",
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use_negative_prompt: bool = False,
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style: str = DEFAULT_STYLE_NAME,
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seed: int = 0,
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width: int = 1024,
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height: int = 1024,
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if check_text(prompt, negative_prompt):
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raise ValueError("Prompt contains restricted words.")
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.Generator().manual_seed(seed)
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negative_prompt = "" # type: ignore
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negative_prompt += default_negative
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options = {
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"prompt": prompt,
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"negative_prompt": negative_prompt,
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"width": width,
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"height": height,
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"guidance_scale": guidance_scale,
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"num_inference_steps":
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"generator": generator,
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"num_images_per_prompt":
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"use_resolution_binning": use_resolution_binning,
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"output_type": "pil",
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}
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examples = [
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"
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"
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"Closeup of blonde woman depth of field, bokeh, shallow focus, minimalism, fujifilm xh2s with Canon EF lens, cinematic --ar 85:128 --v 6.0 --style raw"
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]
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css = '''
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.gradio-container{max-width:
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h1{text-align:center}
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'''
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with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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container=False,
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)
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run_button = gr.Button("Run")
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result = gr.Gallery(label="
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with gr.Accordion("Advanced options", open=False):
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use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
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negative_prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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placeholder="Enter a negative prompt",
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value="(deformed
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visible=True,
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)
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with gr.Row():
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num_inference_steps = gr.Slider(
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label="Steps",
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minimum=10,
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maximum=
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step=1,
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value=
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)
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with gr.Row():
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num_images_per_prompt = gr.Slider(
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visible=True
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)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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with gr.Row(visible=True):
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width = gr.Slider(
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label="Width",
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step=8,
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value=1024,
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)
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with gr.Row():
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guidance_scale = gr.Slider(
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label="Guidance Scale",
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step=0.1,
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value=6,
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)
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style_selection = gr.Radio(
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show_label=True,
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container=True,
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interactive=True,
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choices=STYLE_NAMES,
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value=DEFAULT_STYLE_NAME,
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label="Image Style",
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)
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gr.Examples(
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examples=examples,
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inputs=prompt,
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outputs=[result, seed],
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fn=generate,
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cache_examples=CACHE_EXAMPLES,
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)
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negative_prompt,
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use_negative_prompt,
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style_selection,
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seed,
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width,
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height,
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)
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if __name__ == "__main__":
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demo.queue(max_size=20).launch()
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#!/usr/bin/env python
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#patch 0.04
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#Func() Dalle Collage Moved Midjourney Space
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#Pruned DalleCollage Space
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import os
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import random
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import uuid
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from diffusers import DiffusionPipeline
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from typing import Tuple
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#BaseConditions--
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bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
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bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
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default_negative = os.getenv("default_negative","")
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return True
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return False
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style_list = [
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{
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"name": "3840 x 2160",
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"prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
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},
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{
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"name": "2560 x 1440",
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"prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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},
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{
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"name": "HD+",
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"prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
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},
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{
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"name": "Style Zero",
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"prompt": "{prompt}",
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"negative_prompt": "",
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},
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]
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collage_style_list = [
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{
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"name": "Hi-Res",
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"prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
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},
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{
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"name": "B & W",
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"prompt": "black and white collage of {prompt}. monochromatic, timeless, classic, dramatic contrast",
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"negative_prompt": "colorful, vibrant, bright, flashy",
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},
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{
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"name": "Polaroid",
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"prompt": "collage of polaroid photos featuring {prompt}. vintage style, high contrast, nostalgic, instant film aesthetic",
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"negative_prompt": "digital, modern, low quality, blurry",
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},
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{
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"name": "Watercolor",
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"prompt": "watercolor collage of {prompt}. soft edges, translucent colors, painterly effects",
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"negative_prompt": "digital, sharp lines, solid colors",
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},
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{
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"name": "Cinematic",
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"prompt": "cinematic collage of {prompt}. film stills, movie posters, dramatic lighting",
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"negative_prompt": "static, lifeless, mundane",
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},
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{
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"name": "Nostalgic",
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"prompt": "nostalgic collage of {prompt}. retro imagery, vintage objects, sentimental journey",
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"negative_prompt": "contemporary, futuristic, forward-looking",
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},
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{
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"name": "Vintage",
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"prompt": "vintage collage of {prompt}. aged paper, sepia tones, retro imagery, antique vibes",
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"negative_prompt": "modern, contemporary, futuristic, high-tech",
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},
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{
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"name": "Scrapbook",
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"prompt": "scrapbook style collage of {prompt}. mixed media, hand-cut elements, textures, paper, stickers, doodles",
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"negative_prompt": "clean, digital, modern, low quality",
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},
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{
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"name": "NeoNGlow",
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"prompt": "neon glow collage of {prompt}. vibrant colors, glowing effects, futuristic vibes",
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"negative_prompt": "dull, muted colors, vintage, retro",
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},
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{
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"name": "Geometric",
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"prompt": "geometric collage of {prompt}. abstract shapes, colorful, sharp edges, modern design, high quality",
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"negative_prompt": "blurry, low quality, traditional, dull",
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},
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{
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"name": "Thematic",
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"prompt": "thematic collage of {prompt}. cohesive theme, well-organized, matching colors, creative layout",
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"negative_prompt": "random, messy, unorganized, clashing colors",
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},
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{
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"name": "No Style",
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"prompt": "{prompt}",
|
| 117 |
"negative_prompt": "",
|
| 118 |
},
|
| 119 |
]
|
| 120 |
|
| 121 |
+
filters = {
|
| 122 |
+
"Vivid": {
|
| 123 |
+
"prompt": "extra vivid {prompt}",
|
| 124 |
+
"negative_prompt": "washed out, dull"
|
| 125 |
+
},
|
| 126 |
+
"Playa": {
|
| 127 |
+
"prompt": "{prompt} set in a vast playa",
|
| 128 |
+
"negative_prompt": "forest, mountains"
|
| 129 |
+
},
|
| 130 |
+
"Desert": {
|
| 131 |
+
"prompt": "{prompt} set in a desert landscape",
|
| 132 |
+
"negative_prompt": "ocean, city"
|
| 133 |
+
},
|
| 134 |
+
"West": {
|
| 135 |
+
"prompt": "{prompt} with a western theme",
|
| 136 |
+
"negative_prompt": "eastern, modern"
|
| 137 |
+
},
|
| 138 |
+
"Blush": {
|
| 139 |
+
"prompt": "{prompt} with a soft blush color palette",
|
| 140 |
+
"negative_prompt": "harsh colors, neon"
|
| 141 |
+
},
|
| 142 |
+
"Minimalist": {
|
| 143 |
+
"prompt": "{prompt} with a minimalist design",
|
| 144 |
+
"negative_prompt": "cluttered, ornate"
|
| 145 |
+
},
|
| 146 |
+
|
| 147 |
+
"Zero filter": {
|
| 148 |
+
"prompt": "{prompt}",
|
| 149 |
+
"negative_prompt": ""
|
| 150 |
+
},
|
| 151 |
+
|
| 152 |
+
|
| 153 |
+
}
|
| 154 |
+
|
| 155 |
styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
|
| 156 |
+
collage_styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in collage_style_list}
|
| 157 |
+
filter_styles = {k: (v["prompt"], v["negative_prompt"]) for k, v in filters.items()}
|
| 158 |
STYLE_NAMES = list(styles.keys())
|
| 159 |
+
COLLAGE_STYLE_NAMES = list(collage_styles.keys())
|
| 160 |
+
FILTER_NAMES = list(filters.keys())
|
| 161 |
+
DEFAULT_STYLE_NAME = "3840 x 2160"
|
| 162 |
+
DEFAULT_COLLAGE_STYLE_NAME = "Hi-Res"
|
| 163 |
+
DEFAULT_FILTER_NAME = "Vivid"
|
| 164 |
|
| 165 |
def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
|
| 166 |
+
if style_name in styles:
|
| 167 |
+
p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
|
| 168 |
+
elif style_name in collage_styles:
|
| 169 |
+
p, n = collage_styles.get(style_name, collage_styles[DEFAULT_COLLAGE_STYLE_NAME])
|
| 170 |
+
elif style_name in filter_styles:
|
| 171 |
+
p, n = filter_styles.get(style_name, filter_styles[DEFAULT_FILTER_NAME])
|
| 172 |
+
else:
|
| 173 |
+
p, n = styles[DEFAULT_STYLE_NAME]
|
| 174 |
+
|
| 175 |
if not negative:
|
| 176 |
negative = ""
|
| 177 |
return p.replace("{prompt}", positive), n + negative
|
| 178 |
|
|
|
|
|
|
|
| 179 |
|
| 180 |
|
| 181 |
DESCRIPTION = """## MidJourney
|
|
|
|
| 184 |
"""
|
| 185 |
|
| 186 |
|
|
|
|
|
|
|
|
|
|
| 187 |
if not torch.cuda.is_available():
|
| 188 |
DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
|
| 189 |
|
|
|
|
| 195 |
|
| 196 |
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
|
| 197 |
|
|
|
|
|
|
|
| 198 |
if torch.cuda.is_available():
|
| 199 |
pipe = DiffusionPipeline.from_pretrained(
|
| 200 |
+
"SG161222/RealVisXL_V4.0",
|
| 201 |
torch_dtype=torch.float16,
|
| 202 |
use_safetensors=True,
|
| 203 |
add_watermarker=False,
|
| 204 |
variant="fp16"
|
| 205 |
+
).to(device)
|
| 206 |
+
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 207 |
if ENABLE_CPU_OFFLOAD:
|
| 208 |
pipe.enable_model_cpu_offload()
|
|
|
|
| 209 |
else:
|
| 210 |
+
pipe.to(device)
|
|
|
|
| 211 |
print("Loaded on Device!")
|
| 212 |
+
|
| 213 |
if USE_TORCH_COMPILE:
|
| 214 |
pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
|
|
|
|
| 215 |
print("Model Compiled!")
|
| 216 |
|
| 217 |
+
def save_image(img, path):
|
| 218 |
+
img.save(path)
|
|
|
|
|
|
|
| 219 |
|
| 220 |
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
|
| 221 |
if randomize_seed:
|
|
|
|
| 228 |
negative_prompt: str = "",
|
| 229 |
use_negative_prompt: bool = False,
|
| 230 |
style: str = DEFAULT_STYLE_NAME,
|
| 231 |
+
collage_style: str = DEFAULT_COLLAGE_STYLE_NAME,
|
| 232 |
+
filter_name: str = DEFAULT_FILTER_NAME,
|
| 233 |
+
grid_size: str = "2x2",
|
| 234 |
seed: int = 0,
|
| 235 |
width: int = 1024,
|
| 236 |
height: int = 1024,
|
|
|
|
| 242 |
if check_text(prompt, negative_prompt):
|
| 243 |
raise ValueError("Prompt contains restricted words.")
|
| 244 |
|
| 245 |
+
if collage_style != "No Style":
|
| 246 |
+
prompt, negative_prompt = apply_style(collage_style, prompt, negative_prompt)
|
| 247 |
+
elif filter_name != "No Filter":
|
| 248 |
+
prompt, negative_prompt = apply_style(filter_name, prompt, negative_prompt)
|
| 249 |
+
else:
|
| 250 |
+
prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
|
| 251 |
+
|
| 252 |
seed = int(randomize_seed_fn(seed, randomize_seed))
|
| 253 |
generator = torch.Generator().manual_seed(seed)
|
| 254 |
|
|
|
|
| 256 |
negative_prompt = "" # type: ignore
|
| 257 |
negative_prompt += default_negative
|
| 258 |
|
| 259 |
+
grid_sizes = {
|
| 260 |
+
"2x1": (2, 1),
|
| 261 |
+
"1x2": (1, 2),
|
| 262 |
+
"2x2": (2, 2),
|
| 263 |
+
"2x3": (2, 3),
|
| 264 |
+
"3x2": (3, 2),
|
| 265 |
+
"1x1": (1, 1)
|
| 266 |
+
}
|
| 267 |
+
|
| 268 |
+
grid_size_x, grid_size_y = grid_sizes.get(grid_size, (2, 2))
|
| 269 |
+
num_images = grid_size_x * grid_size_y
|
| 270 |
+
|
| 271 |
options = {
|
| 272 |
"prompt": prompt,
|
| 273 |
"negative_prompt": negative_prompt,
|
| 274 |
"width": width,
|
| 275 |
"height": height,
|
| 276 |
"guidance_scale": guidance_scale,
|
| 277 |
+
"num_inference_steps": 20,
|
| 278 |
"generator": generator,
|
| 279 |
+
"num_images_per_prompt": num_images,
|
| 280 |
"use_resolution_binning": use_resolution_binning,
|
| 281 |
"output_type": "pil",
|
| 282 |
}
|
| 283 |
|
| 284 |
+
torch.cuda.empty_cache() # Clear GPU memory
|
| 285 |
+
images = pipe(**options).images
|
| 286 |
|
| 287 |
+
grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
|
| 288 |
+
|
| 289 |
+
for i, img in enumerate(images[:num_images]):
|
| 290 |
+
grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
|
| 291 |
+
|
| 292 |
+
unique_name = str(uuid.uuid4()) + ".png"
|
| 293 |
+
save_image(grid_img, unique_name)
|
| 294 |
+
return [unique_name], seed
|
| 295 |
|
| 296 |
examples = [
|
| 297 |
+
"Portrait of a beautiful woman in a hat, summer outfit, with freckles on her face, in a close up shot, with sunlight, outdoors, in soft light, with a beach background, looking at the camera, with high resolution photography, in the style of Hasselblad X2D50c --ar 85:128 --v 6.0 --style raw",
|
| 298 |
+
"3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
|
| 299 |
+
"Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
|
| 300 |
"Closeup of blonde woman depth of field, bokeh, shallow focus, minimalism, fujifilm xh2s with Canon EF lens, cinematic --ar 85:128 --v 6.0 --style raw"
|
| 301 |
]
|
| 302 |
|
| 303 |
css = '''
|
| 304 |
+
.gradio-container{max-width: 670px !important}
|
| 305 |
h1{text-align:center}
|
| 306 |
'''
|
| 307 |
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
|
|
|
|
| 321 |
container=False,
|
| 322 |
)
|
| 323 |
run_button = gr.Button("Run")
|
| 324 |
+
result = gr.Gallery(label="Grid", columns=1, preview=True)
|
| 325 |
+
|
| 326 |
+
|
| 327 |
+
with gr.Row(visible=True):
|
| 328 |
+
filter_selection = gr.Radio(
|
| 329 |
+
show_label=True,
|
| 330 |
+
container=True,
|
| 331 |
+
interactive=True,
|
| 332 |
+
choices=FILTER_NAMES,
|
| 333 |
+
value=DEFAULT_FILTER_NAME,
|
| 334 |
+
label="Filter Type",
|
| 335 |
+
)
|
| 336 |
+
|
| 337 |
+
with gr.Row(visible=True):
|
| 338 |
+
style_selection = gr.Radio(
|
| 339 |
+
show_label=True,
|
| 340 |
+
container=True,
|
| 341 |
+
interactive=True,
|
| 342 |
+
choices=STYLE_NAMES,
|
| 343 |
+
value=DEFAULT_STYLE_NAME,
|
| 344 |
+
label="Quality Style",
|
| 345 |
+
)
|
| 346 |
+
|
| 347 |
+
with gr.Row(visible=True):
|
| 348 |
+
collage_style_selection = gr.Radio(
|
| 349 |
+
show_label=True,
|
| 350 |
+
container=True,
|
| 351 |
+
interactive=True,
|
| 352 |
+
choices=COLLAGE_STYLE_NAMES,
|
| 353 |
+
value=DEFAULT_COLLAGE_STYLE_NAME,
|
| 354 |
+
label="Collage Template",
|
| 355 |
+
)
|
| 356 |
+
with gr.Row(visible=True):
|
| 357 |
+
grid_size_selection = gr.Dropdown(
|
| 358 |
+
choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
|
| 359 |
+
value="2x2",
|
| 360 |
+
label="Grid Size"
|
| 361 |
+
)
|
| 362 |
+
|
| 363 |
with gr.Accordion("Advanced options", open=False):
|
| 364 |
use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
|
| 365 |
negative_prompt = gr.Text(
|
| 366 |
label="Negative prompt",
|
| 367 |
max_lines=1,
|
| 368 |
placeholder="Enter a negative prompt",
|
| 369 |
+
value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
|
| 370 |
visible=True,
|
| 371 |
)
|
| 372 |
with gr.Row():
|
| 373 |
num_inference_steps = gr.Slider(
|
| 374 |
label="Steps",
|
| 375 |
minimum=10,
|
| 376 |
+
maximum=30,
|
| 377 |
step=1,
|
| 378 |
+
value=15,
|
| 379 |
)
|
| 380 |
with gr.Row():
|
| 381 |
num_images_per_prompt = gr.Slider(
|
|
|
|
| 394 |
visible=True
|
| 395 |
)
|
| 396 |
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
|
| 397 |
+
|
| 398 |
with gr.Row(visible=True):
|
| 399 |
width = gr.Slider(
|
| 400 |
label="Width",
|
|
|
|
| 410 |
step=8,
|
| 411 |
value=1024,
|
| 412 |
)
|
| 413 |
+
|
| 414 |
with gr.Row():
|
| 415 |
guidance_scale = gr.Slider(
|
| 416 |
label="Guidance Scale",
|
|
|
|
| 419 |
step=0.1,
|
| 420 |
value=6,
|
| 421 |
)
|
| 422 |
+
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 423 |
gr.Examples(
|
| 424 |
examples=examples,
|
| 425 |
inputs=prompt,
|
| 426 |
outputs=[result, seed],
|
| 427 |
fn=generate,
|
| 428 |
+
#cache_examples=True,
|
| 429 |
cache_examples=CACHE_EXAMPLES,
|
| 430 |
)
|
| 431 |
|
|
|
|
| 448 |
negative_prompt,
|
| 449 |
use_negative_prompt,
|
| 450 |
style_selection,
|
| 451 |
+
collage_style_selection,
|
| 452 |
+
filter_selection,
|
| 453 |
+
grid_size_selection,
|
| 454 |
seed,
|
| 455 |
width,
|
| 456 |
height,
|
|
|
|
| 462 |
)
|
| 463 |
|
| 464 |
if __name__ == "__main__":
|
| 465 |
+
demo.queue(max_size=20).launch()
|