Create app.py

app.py

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+import gradio as gr
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+
+processor = AutoImageProcessor.from_pretrained("dimasichsanul/jute_pest_classification")
+model = AutoModelForImageClassification.from_pretrained("dimasichsanul/jute_pest_classification")
+
+def jute_predict(input_image):
+  inputs = processor(input_image, return_tensors='pt')
+  output = model(**inputs)
+
+  labels = ['Beet Armyworm', 'Black Hairy', 'Cutworm', 'Field Cricket', 
+          'Jute Aphid', 'Jute Hairy', 'Jute Red Mite', 'Jute Semilooper', 
+          'Jute Stem Girdler', 'Jute Stem Weevil', 'Leaf Beetle',
+          'Mealybug', 'Pod Borer', 'Scopula Emissaria', 'Termite',
+          'Termite odontotermes (Rambur)', 'Yellow Mite']
+  proba = output.logits.softmax(1)
+
+  label = labels[proba.argmax(1)]
+  value = proba.max().item()
+  return {"score":value, "label":label}
+
+iface = gr.Interface(fn=jute_predict, 
+                     inputs=gr.Image(label="Select jute pest candidate", type="pil"), 
+                     outputs="json",
+                     title="Jute Pest Classification",)
+iface.launch()