Create app.py

app.py

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+import gradio as gr
+import torch
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+model_id = "microsoft/food101-resnet50"
+processor = AutoImageProcessor.from_pretrained(model_id)
+model = AutoModelForImageClassification.from_pretrained(model_id)
+
+def classify_food(image):
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    return model.config.id2label[predicted_class_idx]
+
+interface = gr.Interface(
+    fn=classify_food,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Textbox(),
+    title="Food Image Classification",
+    description="Upload a food image and the model will classify it."
+)
+
+interface.launch()