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import os |
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import random |
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import uuid |
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import json |
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import gradio as gri |
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import numpy as np |
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from PIL import Image |
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import spaces |
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import torch |
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from fooocus import FooocusPipeline |
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from typing import Tuple |
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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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def check_text(prompt, negative=""): |
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for i in bad_words: |
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if i in prompt: |
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return True |
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for i in bad_words_negative: |
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if i in 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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"negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly", |
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}, |
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{ |
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"name": "Photo", |
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"prompt": "cinematic photo {prompt}. 35mm photograph, film, bokeh, professional, 4k, highly detailed", |
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"negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly", |
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}, |
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{ |
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"name": "Cinematic", |
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"prompt": "cinematic still {prompt}. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", |
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"negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured", |
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}, |
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{ |
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"name": "Anime", |
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"prompt": "anime artwork {prompt}. anime style, key visual, vibrant, studio anime, highly detailed", |
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"negative_prompt": "photo, deformed, black and white, realism, disfigured, low contrast", |
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}, |
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{ |
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"name": "3D Model", |
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"prompt": "professional 3d model {prompt}. octane render, highly detailed, volumetric, dramatic lighting", |
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"negative_prompt": "ugly, deformed, noisy, low poly, blurry, painting", |
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}, |
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{ |
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"name": "(No style)", |
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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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DEFAULT_STYLE_NAME = "2560 x 1440" |
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def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]: |
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p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME]) |
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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 = """## MidJourneyHepzeka.com Ücretsiz ve Sınırsız Görsel Üretmek için Yapay Zeka Modeli""" |
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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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MAX_SEED = np.iinfo(np.int32).max |
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CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1" |
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MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048")) |
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USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1" |
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ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1" |
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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 = FooocusPipeline.from_pretrained( |
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"SG161222/RealVisXL_V3.0_Turbo", |
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