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.gitattributes

@@ -35,3 +35,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 fastai_banana_classifier/green_banana.jpg filter=lfs diff=lfs merge=lfs -text
 fastai_banana_classifier/yellow_banana.jpg filter=lfs diff=lfs merge=lfs -text
+green_banana.jpg filter=lfs diff=lfs merge=lfs -text
+yellow_banana.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from fastai.vision.all import *
+
+learn = load_learner('model.pkl')
+labels = ['brown_spots', 'green', 'spoiled', 'yellow']
+
+
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Banana Quality Classifier"
+description = "A banana classifier that can classify bananas into 4 categories based on their quality"
+examples = ['yellow_banana.jpg', 'green_banana.jpg', 'banana_with_brown_spots.jpg', 'black_banana.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    title=title,
+    description=description,
+    examples=examples,
+    interpretation=interpretation,
+    enable_queue=enable_queue
+).launch()

requirements.txt

@@ -0,0 +1,2 @@
+fastai
+scikit-image