Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('model.pkl')
+
+# Original labels from the model
+labels = learn.dls.vocab
+
+# Custom mapping for labels
+custom_labels = {
+    "Other": "Nimeshindwa kutambua picha",
+    "lateblt": "Ukungu wa mwisho wa viazi",
+    "earlyblt": "Ukungu wa mwanzo wa viazi",
+    "healthy": "Jani halina ugonjwa"
+}
+
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    # Map the model's labels to the custom labels
+    return {custom_labels[labels[i]]: float(probs[i]) for i in range(len(labels))}
+
+# Other parameters
+examples = ['image.jpg']
+interpretation = 'default'
+enable_queue = True
+
+# Launch Gradio interface
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3), examples=examples, interpretation=interpretation, enable_queue=enable_queue).launch()