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| #!/usr/bin/env python | |
| #patch 0.04 | |
| #Func() Dalle Collage Moved Midjourney Space | |
| #Pruned DalleCollage Space | |
| import os | |
| import random | |
| import uuid | |
| import json | |
| import gradio as gr | |
| import numpy as np | |
| from PIL import Image | |
| import spaces | |
| import torch | |
| from diffusers import DiffusionPipeline | |
| from typing import Tuple | |
| #BaseConditions-- | |
| bad_words = json.loads(os.getenv('BAD_WORDS', "[]")) | |
| bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]")) | |
| default_negative = os.getenv("default_negative","") | |
| def check_text(prompt, negative=""): | |
| for i in bad_words: | |
| if i in prompt: | |
| return True | |
| for i in bad_words_negative: | |
| if i in negative: | |
| return True | |
| return False | |
| style_list = [ | |
| { | |
| "name": "3840 x 2160", | |
| "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
| "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
| }, | |
| { | |
| "name": "2560 x 1440", | |
| "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
| "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
| }, | |
| { | |
| "name": "HD+", | |
| "prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
| "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
| }, | |
| { | |
| "name": "Style Zero", | |
| "prompt": "{prompt}", | |
| "negative_prompt": "", | |
| }, | |
| ] | |
| collage_style_list = [ | |
| { | |
| "name": "Hi-Res", | |
| "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic", | |
| "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", | |
| }, | |
| { | |
| "name": "B & W", | |
| "prompt": "black and white collage of {prompt}. monochromatic, timeless, classic, dramatic contrast", | |
| "negative_prompt": "colorful, vibrant, bright, flashy", | |
| }, | |
| { | |
| "name": "Polaroid", | |
| "prompt": "collage of polaroid photos featuring {prompt}. vintage style, high contrast, nostalgic, instant film aesthetic", | |
| "negative_prompt": "digital, modern, low quality, blurry", | |
| }, | |
| { | |
| "name": "Watercolor", | |
| "prompt": "watercolor collage of {prompt}. soft edges, translucent colors, painterly effects", | |
| "negative_prompt": "digital, sharp lines, solid colors", | |
| }, | |
| { | |
| "name": "Cinematic", | |
| "prompt": "cinematic collage of {prompt}. film stills, movie posters, dramatic lighting", | |
| "negative_prompt": "static, lifeless, mundane", | |
| }, | |
| { | |
| "name": "Nostalgic", | |
| "prompt": "nostalgic collage of {prompt}. retro imagery, vintage objects, sentimental journey", | |
| "negative_prompt": "contemporary, futuristic, forward-looking", | |
| }, | |
| { | |
| "name": "Vintage", | |
| "prompt": "vintage collage of {prompt}. aged paper, sepia tones, retro imagery, antique vibes", | |
| "negative_prompt": "modern, contemporary, futuristic, high-tech", | |
| }, | |
| { | |
| "name": "Scrapbook", | |
| "prompt": "scrapbook style collage of {prompt}. mixed media, hand-cut elements, textures, paper, stickers, doodles", | |
| "negative_prompt": "clean, digital, modern, low quality", | |
| }, | |
| { | |
| "name": "NeoNGlow", | |
| "prompt": "neon glow collage of {prompt}. vibrant colors, glowing effects, futuristic vibes", | |
| "negative_prompt": "dull, muted colors, vintage, retro", | |
| }, | |
| { | |
| "name": "Geometric", | |
| "prompt": "geometric collage of {prompt}. abstract shapes, colorful, sharp edges, modern design, high quality", | |
| "negative_prompt": "blurry, low quality, traditional, dull", | |
| }, | |
| { | |
| "name": "Thematic", | |
| "prompt": "thematic collage of {prompt}. cohesive theme, well-organized, matching colors, creative layout", | |
| "negative_prompt": "random, messy, unorganized, clashing colors", | |
| }, | |
| { | |
| "name": "No Style", | |
| "prompt": "{prompt}", | |
| "negative_prompt": "", | |
| }, | |
| ] | |
| filters = { | |
| "Vivid": { | |
| "prompt": "extra vivid {prompt}", | |
| "negative_prompt": "washed out, dull" | |
| }, | |
| "Playa": { | |
| "prompt": "{prompt} set in a vast playa", | |
| "negative_prompt": "forest, mountains" | |
| }, | |
| "Desert": { | |
| "prompt": "{prompt} set in a desert landscape", | |
| "negative_prompt": "ocean, city" | |
| }, | |
| "West": { | |
| "prompt": "{prompt} with a western theme", | |
| "negative_prompt": "eastern, modern" | |
| }, | |
| "Blush": { | |
| "prompt": "{prompt} with a soft blush color palette", | |
| "negative_prompt": "harsh colors, neon" | |
| }, | |
| "Minimalist": { | |
| "prompt": "{prompt} with a minimalist design", | |
| "negative_prompt": "cluttered, ornate" | |
| }, | |
| "Zero filter": { | |
| "prompt": "{prompt}", | |
| "negative_prompt": "" | |
| }, | |
| } | |
| styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list} | |
| collage_styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in collage_style_list} | |
| filter_styles = {k: (v["prompt"], v["negative_prompt"]) for k, v in filters.items()} | |
| STYLE_NAMES = list(styles.keys()) | |
| COLLAGE_STYLE_NAMES = list(collage_styles.keys()) | |
| FILTER_NAMES = list(filters.keys()) | |
| DEFAULT_STYLE_NAME = "3840 x 2160" | |
| DEFAULT_COLLAGE_STYLE_NAME = "Hi-Res" | |
| DEFAULT_FILTER_NAME = "Vivid" | |
| def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]: | |
| if style_name in styles: | |
| p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME]) | |
| elif style_name in collage_styles: | |
| p, n = collage_styles.get(style_name, collage_styles[DEFAULT_COLLAGE_STYLE_NAME]) | |
| elif style_name in filter_styles: | |
| p, n = filter_styles.get(style_name, filter_styles[DEFAULT_FILTER_NAME]) | |
| else: | |
| p, n = styles[DEFAULT_STYLE_NAME] | |
| if not negative: | |
| negative = "" | |
| return p.replace("{prompt}", positive), n + negative | |
| DESCRIPTION = """## MidJourney | |
| Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7), Have you tried the stable hamster space? [rb.gy/hfrm2f](http://rb.gy/hfrm2f) | |
| """ | |
| if not torch.cuda.is_available(): | |
| DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>" | |
| MAX_SEED = np.iinfo(np.int32).max | |
| CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1" | |
| MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048")) | |
| USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1" | |
| ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1" | |
| device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
| if torch.cuda.is_available(): | |
| pipe = DiffusionPipeline.from_pretrained( | |
| "----you model goes here-----", | |
| torch_dtype=torch.float16, | |
| use_safetensors=True, | |
| add_watermarker=False, | |
| variant="fp16" | |
| ).to(device) | |
| if ENABLE_CPU_OFFLOAD: | |
| pipe.enable_model_cpu_offload() | |
| else: | |
| pipe.to(device) | |
| print("Loaded on Device!") | |
| if USE_TORCH_COMPILE: | |
| pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True) | |
| print("Model Compiled!") | |
| def save_image(img, path): | |
| img.save(path) | |
| def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: | |
| if randomize_seed: | |
| seed = random.randint(0, MAX_SEED) | |
| return seed | |
| def generate( | |
| prompt: str, | |
| negative_prompt: str = "", | |
| use_negative_prompt: bool = False, | |
| style: str = DEFAULT_STYLE_NAME, | |
| collage_style: str = DEFAULT_COLLAGE_STYLE_NAME, | |
| filter_name: str = DEFAULT_FILTER_NAME, | |
| grid_size: str = "2x2", | |
| seed: int = 0, | |
| width: int = 1024, | |
| height: int = 1024, | |
| guidance_scale: float = 3, | |
| randomize_seed: bool = False, | |
| use_resolution_binning: bool = True, | |
| progress=gr.Progress(track_tqdm=True), | |
| ): | |
| if check_text(prompt, negative_prompt): | |
| raise ValueError("Prompt contains restricted words.") | |
| if collage_style != "No Style": | |
| prompt, negative_prompt = apply_style(collage_style, prompt, negative_prompt) | |
| elif filter_name != "No Filter": | |
| prompt, negative_prompt = apply_style(filter_name, prompt, negative_prompt) | |
| else: | |
| prompt, negative_prompt = apply_style(style, prompt, negative_prompt) | |
| seed = int(randomize_seed_fn(seed, randomize_seed)) | |
| generator = torch.Generator().manual_seed(seed) | |
| if not use_negative_prompt: | |
| negative_prompt = "" # type: ignore | |
| negative_prompt += default_negative | |
| grid_sizes = { | |
| "2x1": (2, 1), | |
| "1x2": (1, 2), | |
| "2x2": (2, 2), | |
| "2x3": (2, 3), | |
| "3x2": (3, 2), | |
| "1x1": (1, 1) | |
| } | |
| grid_size_x, grid_size_y = grid_sizes.get(grid_size, (2, 2)) | |
| num_images = grid_size_x * grid_size_y | |
| options = { | |
| "prompt": prompt, | |
| "negative_prompt": negative_prompt, | |
| "width": width, | |
| "height": height, | |
| "guidance_scale": guidance_scale, | |
| "num_inference_steps": 20, | |
| "generator": generator, | |
| "num_images_per_prompt": num_images, | |
| "use_resolution_binning": use_resolution_binning, | |
| "output_type": "pil", | |
| } | |
| torch.cuda.empty_cache() # Clear GPU memory | |
| images = pipe(**options).images | |
| grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y)) | |
| for i, img in enumerate(images[:num_images]): | |
| grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height)) | |
| unique_name = str(uuid.uuid4()) + ".png" | |
| save_image(grid_img, unique_name) | |
| return [unique_name], seed | |
| examples = [ | |
| "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", | |
| "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)", | |
| "Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic", | |
| "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" | |
| ] | |
| css = ''' | |
| .gradio-container{max-width: 670px !important} | |
| h1{text-align:center} | |
| ''' | |
| with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo: | |
| gr.Markdown(DESCRIPTION) | |
| gr.DuplicateButton( | |
| value="Duplicate Space for private use", | |
| elem_id="duplicate-button", | |
| visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1", | |
| ) | |
| with gr.Group(): | |
| with gr.Row(): | |
| prompt = gr.Text( | |
| label="Prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| container=False, | |
| ) | |
| run_button = gr.Button("Run") | |
| result = gr.Gallery(label="Grid", columns=1, preview=True) | |
| with gr.Row(visible=True): | |
| filter_selection = gr.Radio( | |
| show_label=True, | |
| container=True, | |
| interactive=True, | |
| choices=FILTER_NAMES, | |
| value=DEFAULT_FILTER_NAME, | |
| label="Filter Type", | |
| ) | |
| with gr.Row(visible=True): | |
| style_selection = gr.Radio( | |
| show_label=True, | |
| container=True, | |
| interactive=True, | |
| choices=STYLE_NAMES, | |
| value=DEFAULT_STYLE_NAME, | |
| label="Quality Style", | |
| ) | |
| with gr.Row(visible=True): | |
| collage_style_selection = gr.Radio( | |
| show_label=True, | |
| container=True, | |
| interactive=True, | |
| choices=COLLAGE_STYLE_NAMES, | |
| value=DEFAULT_COLLAGE_STYLE_NAME, | |
| label="Collage Template", | |
| ) | |
| with gr.Row(visible=True): | |
| grid_size_selection = gr.Dropdown( | |
| choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"], | |
| value="2x2", | |
| label="Grid Size" | |
| ) | |
| with gr.Accordion("Advanced options", open=False): | |
| use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True) | |
| negative_prompt = gr.Text( | |
| label="Negative prompt", | |
| max_lines=1, | |
| placeholder="Enter a negative prompt", | |
| 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", | |
| visible=True, | |
| ) | |
| with gr.Row(): | |
| num_inference_steps = gr.Slider( | |
| label="Steps", | |
| minimum=10, | |
| maximum=30, | |
| step=1, | |
| value=15, | |
| ) | |
| with gr.Row(): | |
| num_images_per_prompt = gr.Slider( | |
| label="Images", | |
| minimum=1, | |
| maximum=5, | |
| step=1, | |
| value=2, | |
| ) | |
| seed = gr.Slider( | |
| label="Seed", | |
| minimum=0, | |
| maximum=MAX_SEED, | |
| step=1, | |
| value=0, | |
| visible=True | |
| ) | |
| randomize_seed = gr.Checkbox(label="Randomize seed", value=True) | |
| with gr.Row(visible=True): | |
| width = gr.Slider( | |
| label="Width", | |
| minimum=512, | |
| maximum=2048, | |
| step=8, | |
| value=1024, | |
| ) | |
| height = gr.Slider( | |
| label="Height", | |
| minimum=512, | |
| maximum=2048, | |
| step=8, | |
| value=1024, | |
| ) | |
| with gr.Row(): | |
| guidance_scale = gr.Slider( | |
| label="Guidance Scale", | |
| minimum=0.1, | |
| maximum=20.0, | |
| step=0.1, | |
| value=6, | |
| ) | |
| gr.Examples( | |
| examples=examples, | |
| inputs=prompt, | |
| outputs=[result, seed], | |
| fn=generate, | |
| #cache_examples=True, | |
| cache_examples=CACHE_EXAMPLES, | |
| ) | |
| use_negative_prompt.change( | |
| fn=lambda x: gr.update(visible=x), | |
| inputs=use_negative_prompt, | |
| outputs=negative_prompt, | |
| api_name=False, | |
| ) | |
| gr.on( | |
| triggers=[ | |
| prompt.submit, | |
| negative_prompt.submit, | |
| run_button.click, | |
| ], | |
| fn=generate, | |
| inputs=[ | |
| prompt, | |
| negative_prompt, | |
| use_negative_prompt, | |
| style_selection, | |
| collage_style_selection, | |
| filter_selection, | |
| grid_size_selection, | |
| seed, | |
| width, | |
| height, | |
| guidance_scale, | |
| randomize_seed, | |
| ], | |
| outputs=[result, seed], | |
| api_name="run", | |
| ) | |
| if __name__ == "__main__": | |
| demo.queue(max_size=20).launch() | |