Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# 1) 이미지 캡셔닝 파이프라인 초기화
+captioner = pipeline("image-captioning", model="Salesforce/blip-image-captioning-base")
+
+# 2) (옵션) 스타일 변환 함수
+def style_convert(raw_caption, style):
+    if style == "TOEIC Speaking Part 1":
+        # Part 1: “What do you see in the picture?”
+        # 답변: “I see ~.” 한 문장
+        return f"Q: What do you see in the picture?\nA: {raw_caption.capitalize()}."
+    elif style == "IELTS Describe a Photo":
+        return f"Describe the photo in two sentences:\n1. {raw_caption.capitalize()}.\n2. It also shows the context of daily life."
+    else:
+        return raw_caption
+
+# 3) Gradio 인터페이스 함수
+def generate_caption(image, style):
+    # 3.1 이미지 캡셔닝
+    result = captioner(image, max_length=30, num_beams=3)[0]["caption"]
+    # 3.2 스타일 변환
+    return style_convert(result, style)
+
+# 4) Gradio Blocks 정의
+with gr.Blocks() as demo:
+    gr.Markdown("## 📸 이미지 캡셔닝 → English Test 스타일 문장 생성")
+    with gr.Row():
+        img_in = gr.Image(type="pil", label="Upload Image")
+        style_sel = gr.Dropdown(
+            choices=["Raw Caption", "TOEIC Speaking Part 1", "IELTS Describe a Photo"],
+            value="TOEIC Speaking Part 1",
+            label="시험 형식 선택"
+        )
+    output = gr.Textbox(label="Generated Caption", lines=4)
+    btn = gr.Button("Generate")
+    btn.click(fn=generate_caption, inputs=[img_in, style_sel], outputs=output)
+
+# 5) 앱 실행
+if __name__ == "__main__":
+    demo.launch()