Upload app.py

app.py

@@ -0,0 +1,29 @@
+
+import torch
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import gradio as gr
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+def predict(image):
+    processor = AutoImageProcessor.from_pretrained("linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification")
+    model = AutoModelForImageClassification.from_pretrained("linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification").to(device)
+    model.eval()
+
+    inputs = processor(images=image, return_tensors="pt").to(device)
+    with torch.no_grad():
+        logits = model(**inputs).logits
+        predicted_class = logits.argmax(-1).item()
+        class_name = model.config.id2label.get(predicted_class, "Unknown")
+    return class_name
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(),
+    title="Plant Disease Classifier",
+    description="Upload a leaf image to predict plant disease."
+)
+
+iface.launch()