Create app.py

app.py

@@ -0,0 +1,17 @@
+import gradio as gr
+from fastai.vision.all import *
+import skimage
+learn = load_learner('fire_smoke_export.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))}
+ 
+title = "Fire and Smoke Detector"
+description = "Fire and Smoke classifier created with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+article="<p style='text-align: center'><a href='https://github.com/mldurga/projects/blob/master/Fire_smoke_detector.ipynb' target='_blank'>Blog post</a></p>"
+examples = ['Neutral1.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,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()