Update app.py
Browse files
app.py
CHANGED
@@ -14,6 +14,10 @@ import random
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import time
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import requests
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import pandas as pd
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#Load prompts for randomization
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df = pd.read_csv('prompts.csv', header=None)
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@@ -309,12 +313,18 @@ def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps
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).images[0]
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return final_image
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def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2, randomize_seed, seed, width, height, loras_state, progress=gr.Progress(track_tqdm=True)):
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if not selected_indices:
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raise gr.Error("You must select at least one LoRA before proceeding.")
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selected_loras = [loras_state[idx] for idx in selected_indices]
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# Build the prompt with trigger words
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prepends = []
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appends = []
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import time
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import requests
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import pandas as pd
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from transformers import pipeline
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# 번역 모델 로드
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
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#Load prompts for randomization
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df = pd.read_csv('prompts.csv', header=None)
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).images[0]
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return final_image
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def run_lora(prompt, image_input, image_strength, cfg_scale, steps, selected_indices, lora_scale_1, lora_scale_2, randomize_seed, seed, width, height, loras_state, progress=gr.Progress(track_tqdm=True)):
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# 한글 감지 및 번역
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if any('\u3131' <= char <= '\u318E' or '\uAC00' <= char <= '\uD7A3' for char in prompt):
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translated = translator(prompt, max_length=512)[0]['translation_text']
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print(f"Original prompt: {prompt}")
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print(f"Translated prompt: {translated}")
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prompt = translated
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if not selected_indices:
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raise gr.Error("You must select at least one LoRA before proceeding.")
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# Build the prompt with trigger words
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prepends = []
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appends = []
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