Create app.py

app.py

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+import gradio as gr
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+from PIL import Image
+import torch
+
+# 모델과 feature extractor 로드
+model_name = "shinyice/densenet121-dog-emotions"
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name)
+model = AutoModelForImageClassification.from_pretrained(model_name)
+
+def predict_emotion(image):
+    inputs = feature_extractor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+        predicted_class_idx = logits.argmax(-1).item()
+        return model.config.id2label[predicted_class_idx]
+
+# Gradio 인터페이스 생성
+interface = gr.Interface(
+    fn=predict_emotion,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs="text",
+    title="Dog Emotion Recognition",
+    description="Upload an image of your dog and get its predicted emotion."
+)
+
+interface.launch()