let's deploy to huggingface spaces

app.py

@@ -1,2 +1,15 @@
 from fastai.vision.all import *
-learn = load_learner('drive/MyDrive/cig_detector/roboflow/cig_detector_2.pkl')
+learn = load_learner('cig_detector_2.pkl')
+
+labels = learn.dls.vocab
+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))}
+
+import gradio as gr
+
+title = "Smoking Classifier"
+description = "A smoking, not smoking classifier trained with fastai."
+examples = ['smoking1.jpg', 'smoking2.jpg', 'not_smoking.jpg']
+gr.Interface(title=title, description=description, examples=examples,fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)

requirements.txt

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