Upload app.py

app.py

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+from transformers import BlipProcessor, BlipForConditionalGeneration
+from PIL import Image
+import torch
+import gradio as gr
+import random
+
+# Device 설정
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"🚀 Using device: {device}")
+
+# 모델 로딩
+print("📦 Loading BLIP model...")
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to(device)
+print("✅ Model loaded successfully!")
+
+# 후킹 템플릿
+def generate_hook_title(caption):
+    templates = [
+        f"You won't believe this: {caption}",
+        f"This is what happens when {caption.lower()}",
+        f"{caption}? Now that's a twist!",
+        f"{caption} – but it’s not what you think!",
+        f"When {caption.lower()}, something unexpected happens 😮",
+    ]
+    return random.choice(templates)
+
+# 처리 함수
+def process_image(image):
+    inputs = processor(image, return_tensors="pt").to(device)
+    outputs = model.generate(**inputs)
+    caption = processor.decode(outputs[0], skip_special_tokens=True)
+    hook_title = generate_hook_title(caption)
+    return hook_title
+
+# Gradio 인터페이스
+demo = gr.Interface(
+    fn=process_image,
+    inputs=gr.Image(type="pil", label="📸 Upload your YouTube thumbnail"),
+    outputs=gr.Textbox(label="🔥 Catchy English Title"),
+    title="🎬 YouTube Thumbnail Hook Title Generator",
+    description="Upload a thumbnail image and get a catchy, AI-generated English title!"
+)
+
+if __name__ == "__main__":
+    demo.launch()