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Delete app-backup.py

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  1. app-backup.py +0 -117
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@@ -1,117 +0,0 @@
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- import random
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- import gradio as gr
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- import numpy as np
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- import torch
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- import spaces
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- from diffusers import FluxPipeline
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- from PIL import Image
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- from diffusers.utils import export_to_gif
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- from transformers import pipeline
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-
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- HEIGHT = 256
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- WIDTH = 1024
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- MAX_SEED = np.iinfo(np.int32).max
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-
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- device = "cuda" if torch.cuda.is_available() else "cpu"
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- pipe = FluxPipeline.from_pretrained(
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- "black-forest-labs/FLUX.1-dev",
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- torch_dtype=torch.bfloat16
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- ).to(device)
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-
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- translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
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-
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- def split_image(input_image, num_splits=4):
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- output_images = []
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- for i in range(num_splits):
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- left = i * 256
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- right = (i + 1) * 256
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- box = (left, 0, right, 256)
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- output_images.append(input_image.crop(box))
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- return output_images
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-
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- def translate_to_english(text):
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- return translator(text)[0]['translation_text']
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-
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- @spaces.GPU()
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- def predict(prompt, seed=42, randomize_seed=False, guidance_scale=5.0, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
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- if any('\u3131' <= char <= '\u318E' or '\uAC00' <= char <= '\uD7A3' for char in prompt):
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- prompt = translate_to_english(prompt)
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-
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- prompt_template = f"""
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- A side by side 4 frame image showing consecutive stills from a looped gif moving from left to right. The gif is of {prompt}.
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- """
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-
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- if randomize_seed:
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- seed = random.randint(0, MAX_SEED)
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-
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- image = pipe(
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- prompt=prompt_template,
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- guidance_scale=guidance_scale,
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- num_inference_steps=num_inference_steps,
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- num_images_per_prompt=1,
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- generator=torch.Generator("cpu").manual_seed(seed),
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- height=HEIGHT,
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- width=WIDTH
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- ).images[0]
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-
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- return export_to_gif(split_image(image, 4), "flux.gif", fps=4), image, seed
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-
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- css = """
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- footer { visibility: hidden;}
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- """
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-
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- examples = [
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- "๊ณ ์–‘์ด๊ฐ€ ๊ณต์ค‘์—์„œ ๋ฐœ์„ ํ”๋“œ๋Š” ๋ชจ์Šต",
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- "ํŒฌ๋”๊ฐ€ ์—‰๋ฉ์ด๋ฅผ ์ขŒ์šฐ๋กœ ํ”๋“œ๋Š” ๋ชจ์Šต",
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- "๊ฝƒ์ด ํ”ผ์–ด๋‚˜๋Š” ๊ณผ์ •"
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- ]
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-
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- with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange", css=css) as demo:
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- with gr.Column(elem_id="col-container"):
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- with gr.Row():
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- prompt = gr.Text(label="ํ”„๋กฌํ”„ํŠธ", show_label=False, max_lines=1, placeholder="ํ”„๋กฌํ”„ํŠธ๋ฅผ ์ž…๋ ฅํ•˜์„ธ์š”")
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- submit = gr.Button("์ œ์ถœ", scale=0)
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- output = gr.Image(label="GIF", show_label=False)
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- output_stills = gr.Image(label="์Šคํ‹ธ ์ด๋ฏธ์ง€", show_label=False, elem_id="stills")
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-
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- with gr.Accordion("๊ณ ๊ธ‰ ์„ค์ •", open=False):
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- seed = gr.Slider(
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- label="์‹œ๋“œ",
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- minimum=0,
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- maximum=MAX_SEED,
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- step=1,
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- value=0,
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- )
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- randomize_seed = gr.Checkbox(label="์‹œ๋“œ ๋ฌด์ž‘์œ„ํ™”", value=True)
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- with gr.Row():
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- guidance_scale = gr.Slider(
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- label="๊ฐ€์ด๋˜์Šค ์Šค์ผ€์ผ",
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- minimum=1,
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- maximum=15,
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- step=0.1,
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- value=3.5,
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- )
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- num_inference_steps = gr.Slider(
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- label="์ถ”๋ก  ๋‹จ๊ณ„ ์ˆ˜",
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- minimum=1,
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- maximum=50,
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- step=1,
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- value=28,
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- )
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-
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- gr.Examples(
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- examples=examples,
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- fn=predict,
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- inputs=[prompt],
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- outputs=[output, output_stills, seed],
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- cache_examples="lazy"
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- )
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-
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- gr.on(
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- triggers=[submit.click, prompt.submit],
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- fn=predict,
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- inputs=[prompt, seed, randomize_seed, guidance_scale, num_inference_steps],
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- outputs=[output, output_stills, seed]
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- )
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-
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- demo.launch()