Create app.py

app.py

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+import torch
+from PIL import Image
+import requests
+import gradio as gr
+from torchvision import transforms
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+
+# Load model and extractor
+model_id = "Adriana213/vgg16-food-classification"
+model = AutoModelForImageClassification.from_pretrained(model_id)
+extractor = AutoFeatureExtractor.from_pretrained(model_id)
+
+# Transform image to model input
+def transform_image(img):
+    return extractor(images=img, return_tensors="pt")["pixel_values"]
+
+# Predict function
+def detect_food(image):
+    inputs = transform_image(image)
+    with torch.no_grad():
+        outputs = model(inputs)
+        probs = torch.nn.functional.softmax(outputs.logits, dim=1)[0]
+
+    # Get top 5 predictions
+    topk = torch.topk(probs, 5)
+    labels = [model.config.id2label[i.item()] for i in topk.indices]
+    scores = [round(i.item() * 100, 2) for i in topk.values]
+
+    results = "\n".join([f"{label}: {score}%" for label, score in zip(labels, scores)])
+    return results
+
+# Gradio UI
+gr.Interface(
+    fn=detect_food,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="🍔 Ultimate Food Detector",
+    description="Upload a food image. Get the dish names. Auto chef mode enabled. 🔥",
+    allow_flagging="never"
+).launch()