Update app-backup.py

app-backup.py

@@ -7,11 +7,21 @@ from PIL import Image
 import spaces
 from diffusers import DiffusionPipeline, AutoencoderTiny, AutoencoderKL
 from live_preview_helpers import calculate_shift, retrieve_timesteps, flux_pipe_call_that_returns_an_iterable_of_images
-
 from huggingface_hub import hf_hub_download, HfFileSystem, ModelCard, snapshot_download
 import copy
 import random
 import time
+from transformers import pipeline
+
+# 번역 모델 초기화
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
+
+# 프롬프트 처리 함수 추가
+def process_prompt(prompt):
+    if any('\u3131' <= char <= '\u3163' or '\uac00' <= char <= '\ud7a3' for char in prompt):
+        translated = translator(prompt)[0]['translation_text']
+        return prompt, translated
+    return prompt, prompt
 
 # Load LoRAs from JSON file
 with open('loras.json', 'r') as f:
@@ -48,9 +58,9 @@ class calculateDuration:
 
 def update_selection(evt: gr.SelectData, width, height):
     selected_lora = loras[evt.index]
-    new_placeholder = f"Type a prompt for {selected_lora['title']}"
+    new_placeholder = f"{selected_lora['title']}를 위한 프롬프트를 입력하세요"
     lora_repo = selected_lora["repo"]
-    updated_text = f"### Selected: [{lora_repo}](https://huggingface.co/{lora_repo}) ✨"
+    updated_text = f"### 선택됨: [{lora_repo}](https://huggingface.co/{lora_repo}) ✨"
     if "aspect" in selected_lora:
         if selected_lora["aspect"] == "portrait":
             width = 768
@@ -73,7 +83,7 @@ def update_selection(evt: gr.SelectData, width, height):
 def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scale, progress):
     pipe.to("cuda")
     generator = torch.Generator(device="cuda").manual_seed(seed)
-    with calculateDuration("Generating image"):
+    with calculateDuration("이미지 생성"):
         # Generate image
         for img in pipe.flux_pipe_call_that_returns_an_iterable_of_images(
             prompt=prompt_mash,
@@ -90,33 +100,36 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, lora_scal
 
 def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
     if selected_index is None:
-        raise gr.Error("You must select a LoRA before proceeding.")
+        raise gr.Error("진행하기 전에 LoRA를 선택해야 합니다.")
+    
+    original_prompt, english_prompt = process_prompt(prompt)
+    
     selected_lora = loras[selected_index]
     lora_path = selected_lora["repo"]
     trigger_word = selected_lora["trigger_word"]
     if(trigger_word):
         if "trigger_position" in selected_lora:
             if selected_lora["trigger_position"] == "prepend":
-                prompt_mash = f"{trigger_word} {prompt}"
+                prompt_mash = f"{trigger_word} {english_prompt}"
             else:
-                prompt_mash = f"{prompt} {trigger_word}"
+                prompt_mash = f"{english_prompt} {trigger_word}"
         else:
-            prompt_mash = f"{trigger_word} {prompt}"
+            prompt_mash = f"{trigger_word} {english_prompt}"
     else:
-        prompt_mash = prompt
+        prompt_mash = english_prompt
 
-    with calculateDuration("Unloading LoRA"):
+    with calculateDuration("LoRA 언로드"):
         pipe.unload_lora_weights()
         
     # Load LoRA weights
-    with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
+    with calculateDuration(f"{selected_lora['title']}의 LoRA 가중치 로드"):
         if "weights" in selected_lora:
             pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
         else:
             pipe.load_lora_weights(lora_path)
 
     # Set random seed for reproducibility
-    with calculateDuration("Randomizing seed"):
+    with calculateDuration("시드 무작위화"):
         if randomize_seed:
             seed = random.randint(0, MAX_SEED)
 
@@ -129,9 +142,10 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
         step_counter+=1
         final_image = image
         progress_bar = f'<div class="progress-container"><div class="progress-bar" style="--current: {step_counter}; --total: {steps};"></div></div>'
-        yield image, seed, gr.update(value=progress_bar, visible=True)
+        yield image, seed, gr.update(value=progress_bar, visible=True), original_prompt, english_prompt
         
-    yield final_image, seed, gr.update(value=progress_bar, visible=False)
+    yield final_image, seed, gr.update(value=progress_bar, visible=False), original_prompt, english_prompt
+
 
 def get_huggingface_safetensors(link):
   split_link = link.split("/")
@@ -216,48 +230,52 @@ footer {
 }
 """
 
+
 with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as app:
 
     selected_index = gr.State(None)
     with gr.Row():
         with gr.Column(scale=3):
-            prompt = gr.Textbox(label="Prompt", lines=1, placeholder="Type a prompt after selecting a LoRA")
+            prompt = gr.Textbox(label="프롬프트", lines=1, placeholder="LoRA를 선택한 후 프롬프트를 입력하세요 (한글 또는 영어)")
         with gr.Column(scale=1, elem_id="gen_column"):
-            generate_button = gr.Button("Generate", variant="primary", elem_id="gen_btn")
+            generate_button = gr.Button("생성", variant="primary", elem_id="gen_btn")
     with gr.Row():
         with gr.Column():
             selected_info = gr.Markdown("")
             gallery = gr.Gallery(
                 [(item["image"], item["title"]) for item in loras],
-                label="LoRA Gallery",
+                label="LoRA 갤러리",
                 allow_preview=False,
                 columns=3,
                 elem_id="gallery"
             )
             with gr.Group():
-                custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path", placeholder="multimodalart/vintage-ads-flux")
-                gr.Markdown("[Check the list of FLUX LoRas](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list")
+                custom_lora = gr.Textbox(label="커스텀 LoRA", info="LoRA Hugging Face 경로", placeholder="multimodalart/vintage-ads-flux")
+                gr.Markdown("[FLUX LoRA 목록 확인](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list")
             custom_lora_info = gr.HTML(visible=False)
-            custom_lora_button = gr.Button("Remove custom LoRA", visible=False)
+            custom_lora_button = gr.Button("커스텀 LoRA 제거", visible=False)
         with gr.Column():
             progress_bar = gr.Markdown(elem_id="progress",visible=False)
-            result = gr.Image(label="Generated Image")
+            result = gr.Image(label="생성된 이미지")
+            original_prompt_display = gr.Textbox(label="원본 프롬프트")
+            english_prompt_display = gr.Textbox(label="영어 프롬프트")
 
     with gr.Row():
-        with gr.Accordion("Advanced Settings", open=False):
+        with gr.Accordion("고급 설정", open=False):
             with gr.Column():
                 with gr.Row():
-                    cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
-                    steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
+                    cfg_scale = gr.Slider(label="CFG 스케일", minimum=1, maximum=20, step=0.5, value=3.5)
+                    steps = gr.Slider(label="스텝", minimum=1, maximum=50, step=1, value=28)
                 
                 with gr.Row():
-                    width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
-                    height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024)
+                    width = gr.Slider(label="너비", minimum=256, maximum=1536, step=64, value=1024)
+                    height = gr.Slider(label="높이", minimum=256, maximum=1536, step=64, value=1024)
                 
                 with gr.Row():
-                    randomize_seed = gr.Checkbox(True, label="Randomize seed")
-                    seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
-                    lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=3, step=0.01, value=0.95)
+                    randomize_seed = gr.Checkbox(True, label="시드 무작위화")
+                    seed = gr.Slider(label="시드", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
+                    lora_scale = gr.Slider(label="LoRA 스케일", minimum=0, maximum=3, step=0.01, value=0.95)
+
 
     gallery.select(
         update_selection,
@@ -273,11 +291,12 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as app:
         remove_custom_lora,
         outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, custom_lora]
     )
+
     gr.on(
         triggers=[generate_button.click, prompt.submit],
         fn=run_lora,
         inputs=[prompt, cfg_scale, steps, selected_index, randomize_seed, seed, width, height, lora_scale],
-        outputs=[result, seed, progress_bar]
+        outputs=[result, seed, progress_bar, original_prompt_display, english_prompt_display]
     )
 
 app.queue()