Create app.py

app.py

@@ -0,0 +1,19 @@
+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('resnet_emoji50.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 = "Window/Damaged_Window Classifier"
+description = "A Window/Damaged_Window classifier trained on the google random images. Please use the examples to try it out. Created as a demo."
+examples = ['00000007.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()