Create app.py

app.py

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+import pickle
+import cv2
+from fastai.vision.all import *
+import gradio as gr
+
+im_size = (1152, 768)
+with open("learn.pkl", 'rb') as f:
+    model = pickle.load(f)
+
+def predict_mask(file):
+    img = cv2.imdecode(np.frombuffer(file.read(), np.uint8), cv2.IMREAD_GRAYSCALE)
+    img = cv2.resize(img, im_size)
+    pred = model.predict(img)
+    return pred[0]
+
+iface = gr.Interface(fn=predict_mask, 
+                     inputs=gr.inputs.Image(label="Upload Image"), 
+                     outputs="image",
+                     capture_session=True,
+                     interpretation="default")
+
+if __name__ == "__main__":
+    iface.launch()