predictions for leak detection

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner("model.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 = "Leak Detection"
+description = "Analyze a photograph of a wellhead and predict whether or not there is a leak."
+interpretation = "default"
+enable_queue = True
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(224, 224)),
+    outputs=gr.outputs.Label(num_top_classes=2),
+    title=title,
+    description=description,
+    interpretation=interpretation,
+    enable_queue=enable_queue,
+).launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2358e9734318c8370cbb0ba7c077352a17d7aaa34a0d0cd133afd361b3020459
+size 46961509

requirements.txt

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+fastai
+scikit-image