Create app-backup.py

app-backup.py

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+import random
+import os
+import uuid
+from datetime import datetime
+import gradio as gr
+import numpy as np
+import spaces
+import torch
+from diffusers import DiffusionPipeline
+from PIL import Image
+
+# Create permanent storage directory
+SAVE_DIR = "saved_images"  # Gradio will handle the persistence
+if not os.path.exists(SAVE_DIR):
+    os.makedirs(SAVE_DIR, exist_ok=True)
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+repo_id = "black-forest-labs/FLUX.1-dev"
+adapter_id = "seawolf2357/kim-korea"  # 특정 정치인을 학습한 LoRA 모델
+
+pipeline = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
+pipeline.load_lora_weights(adapter_id)
+pipeline = pipeline.to(device)
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 1024
+
+def save_generated_image(image, prompt):
+    # Generate unique filename with timestamp
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    unique_id = str(uuid.uuid4())[:8]
+    filename = f"{timestamp}_{unique_id}.png"
+    filepath = os.path.join(SAVE_DIR, filename)
+    
+    # Save the image
+    image.save(filepath)
+    
+    # Save metadata
+    metadata_file = os.path.join(SAVE_DIR, "metadata.txt")
+    with open(metadata_file, "a", encoding="utf-8") as f:
+        f.write(f"{filename}|{prompt}|{timestamp}\n")
+    
+    return filepath
+
+@spaces.GPU(duration=60)
+def inference(
+    prompt,
+    seed=42,
+    randomize_seed=True,
+    width=1024,
+    height=768,
+    guidance_scale=3.5,
+    num_inference_steps=30,
+    lora_scale=1.0,
+    progress=None,
+):
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator(device=device).manual_seed(int(seed))
+    
+    image = pipeline(
+        prompt=prompt,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
+        width=width,
+        height=height,
+        generator=generator,
+        joint_attention_kwargs={"scale": lora_scale},
+    ).images[0]
+    
+    # Save the generated image
+    filepath = save_generated_image(image, prompt)
+    
+    # Return just the image and seed
+    return image, seed
+
+# 예시 문구: 특정 정치인 Mr. KIM의 다양한 상황을 묘사
+
+examples = [
+    "Mr. KIM holding up a 'Fighting!' banner with both hands, showing patriotic pride and determination for national excellence. ",   
+    "Mr. KIM raising both arms in celebration with a triumphant expression, showing victory and hope for the future.",
+    "Mr. KIM jogging in a park wearing athletic gear, demonstrating healthy lifestyle and energetic leadership qualities.",  
+    "Mr. KIM warmly shaking hands with female citizens in a crowded street, showing genuine care and connection with women voters. ",
+    "Mr. KIM at a campaign rally, pointing toward the horizon with an inspiring gesture while female and kids audience members applaud.  ",
+    "Mr. KIM participating in a community event, surrounded by enthusiastic female supporters cheering ",
+    "Mr. KIM visiting a local market, engaging in friendly conversation with female vendors and shopkeepers. ",
+    "Mr. KIM walking through a university campus, discussing education policies with female students and professors. ",    
+    "Mr. KIM delivering a powerful speech in front of a large crowd with confident gestures and determined expression. ",
+    "Mr. KIM in a dynamic interview setting, passionately outlining his visions for the future.",
+    "Mr. KIM preparing for an important debate, surrounded by paperwork, looking focused and resolute. ",
+]
+
+# UI를 붉은 계열 그라디에이션으로 디자인
+custom_css = """
+:root {
+    --color-primary: #8F1A3A; /* 붉은 톤의 메인 컬러 */
+    --color-secondary: #FF4B4B; /* 포인트 컬러(밝은 빨강) */
+    --background-fill-primary: linear-gradient(to right, #FFF5F5, #FED7D7, #FEB2B2);
+}
+footer {
+    visibility: hidden;
+}
+.gradio-container {
+    background: var(--background-fill-primary);
+}
+.title {
+    color: var(--color-primary) !important;
+    font-size: 3rem !important;
+    font-weight: 700 !important;
+    text-align: center;
+    margin: 1rem 0;
+    text-shadow: 2px 2px 4px rgba(0,0,0,0.05);
+    font-family: 'Playfair Display', serif;
+}
+.subtitle {
+    color: #4A5568 !important;
+    font-size: 1.2rem !important;
+    text-align: center;
+    margin-bottom: 1.5rem;
+    font-style: italic;
+}
+.collection-link {
+    text-align: center;
+    margin-bottom: 2rem;
+    font-size: 1.1rem;
+}
+.collection-link a {
+    color: var(--color-primary);
+    text-decoration: underline;
+    transition: color 0.3s ease;
+}
+.collection-link a:hover {
+    color: var(--color-secondary);
+}
+.model-description {
+    background-color: rgba(255, 255, 255, 0.8);
+    border-radius: 12px;
+    padding: 24px;
+    margin: 20px 0;
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.05);
+    border-left: 5px solid var(--color-primary);
+}
+button.primary {
+    background-color: var(--color-primary) !important;
+    transition: all 0.3s ease;
+    color: #fff !important;
+}
+button:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 5px 15px rgba(0,0,0,0.1);
+}
+.input-container {
+    border-radius: 10px;
+    box-shadow: 0 2px 8px rgba(0,0,0,0.05);
+    background-color: rgba(255, 255, 255, 0.6);
+    padding: 20px;
+    margin-bottom: 1rem;
+}
+.advanced-settings {
+    margin-top: 1rem;
+    padding: 1rem;
+    border-radius: 10px;
+    background-color: rgba(255, 255, 255, 0.6);
+}
+.example-region {
+    background-color: rgba(255, 255, 255, 0.5);
+    border-radius: 10px;
+    padding: 1rem;
+    margin-top: 1rem;
+}
+"""
+
+with gr.Blocks(css=custom_css, analytics_enabled=False) as demo:
+    gr.HTML('<div class="title">Mr. KIM in KOREA</div>')
+    
+    # 컬렉션 링크 또는 안내문을 필요 시 수정/삭제
+    gr.HTML('<div class="collection-link"><a href="https://huggingface.co/collections/openfree/painting-art-ai-681453484ec15ef5978bbeb1" target="_blank">Visit the LoRA Model Collection</a></div>')
+    
+    # 모델 설명: 특정 정치인에 대한 LoRA 모델임을 언급
+    with gr.Group(elem_classes="model-description"):
+        gr.HTML("""
+        <p>
+        본 모델은 연구 목적으로 특정인의 얼굴과 외모를 학습한 LoRA 모델입니다.<br>
+        목적외의 용도로 무단 사용 않도록 유의해 주세요.<br>
+        (예시 prompt 사용 시 반드시 'kim'을 포함하여야 최적의 결과를 얻을 수 있습니다.)
+        </p>
+        """)
+
+    # 메인 UI
+    with gr.Column(elem_id="col-container"):
+        with gr.Row(elem_classes="input-container"):
+            prompt = gr.Text(
+                label="Prompt",
+                max_lines=1,
+                placeholder="Enter your prompt (add [trigger] at the end)",
+                value=examples[0]  # 기본 예시
+            )
+            run_button = gr.Button("Generate", variant="primary", scale=0)
+
+        result = gr.Image(label="Generated Image")
+        seed_output = gr.Number(label="Seed", visible=True)
+
+        with gr.Accordion("Advanced Settings", open=False, elem_classes="advanced-settings"):
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=42,
+            )
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=768,
+                )
+
+            with gr.Row():
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=0.0,
+                    maximum=10.0,
+                    step=0.1,
+                    value=3.5,
+                )
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=30,
+                )
+                lora_scale = gr.Slider(
+                    label="LoRA scale",
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.1,
+                    value=1.0,
+                )
+
+        with gr.Group(elem_classes="example-region"):
+            gr.Markdown("### Examples")
+            gr.Examples(
+                examples=examples,
+                inputs=prompt,
+                outputs=None,  # Don't auto-run examples
+                fn=None,       # No function to run for examples - just fill the prompt
+                cache_examples=False,
+            )
+
+    # 이벤트 핸들러
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=inference,
+        inputs=[
+            prompt,
+            seed,
+            randomize_seed,
+            width,
+            height,
+            guidance_scale,
+            num_inference_steps,
+            lora_scale,
+        ],
+        outputs=[result, seed_output],
+    )
+
+demo.queue()
+demo.launch()