Update app.py

app.py

@@ -1,26 +1,15 @@
 import gradio as gr
-from transformers import pipeline, AutoTokenizer
+from transformers import pipeline
 
-# 加载模型和分词器
-model_name = "bert-base-uncased"
-model = pipeline("text-classification", model=model_name, tokenizer=model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-# 定义 Gradio 接口
-def classify_text(text):
-    # 对输入文本进行分词
-    inputs = tokenizer(text, return_tensors="pt")
-    # 使用模型进行预测
-    outputs = model(inputs)
-    # 获取预测结果
-    label = outputs[0]["label"]
-    score = outputs[0]["score"]
-    return f"Label: {label}, Score: {score:.2f}"
+def predict(image):
+    predictions = pipeline(image)
+    return {p["label"]: p["score"] for p in predictions}
 
-iface = gr.Interface(
-    fn=classify_text,
-    inputs=gr.inputs.Textbox(),
-    outputs=gr.outputs.HTML(),
-)
-
-iface.launch()
+gr.Interface(
+    predict,
+    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
+    outputs=gr.outputs.Label(num_top_classes=2),
+    title="Hot Dog? Or Not?",
+).launch()