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app.py

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+from fastai.vision.all import *
+import gradio as gr
+import pathlib
+
+plt = platform.system()
+if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
+
+file = open('model.pkl', 'rb')
+temp = pickle.load(file)
+file.close()
+
+infer = temp['model']
+data_map = [f'{item["name"]} ({item["botanical_name"]})' for item in temp['map']]
+
+def classify(img):
+    _, _, probs = infer.predict(img)
+    return dict(map(lambda x: (data_map[int(infer.dls.vocab[x[0]])], float(x[1])), enumerate(probs)))
+
+image = gr.inputs.Image(shape=(224, 224))
+label = gr.outputs.Label(num_top_classes=3)
+iface = gr.Interface(fn=classify, title='Indoor Plant Classifier', inputs=image, outputs=label)
+iface.launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:eba9ccb36ff60c1b977aff8346d5f13eae20ff851e23e76af42bea6531111569
+size 355617495