initial app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('export.pkl')
+labels = learn.dls.vocab
+def predict(img):
+    img = img.resize((512, 512))
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Camel or a Llama ?"
+examples = ['/content/Llama_or_not/Llama/123e64ba-45e6-4f8b-b055-8762d6a9a347.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=3),
+    title=title,
+    examples=examples,
+).launch(share=True)