Create app.py

app.py

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+from fastai.vision.core import PILImageBW, TensorImageBW
+from datasets import ClassLabel
+import gradio as gr
+from fastai.learner import load_learner
+
+def get_image_attr(x): return x['image']
+def get_target_attr(x): return x['target']
+
+def img2tensor(im: Image.Image):
+  return TensorImageBW(array(im)).unsqueeze(0)
+
+classLabel = ClassLabel(names=['T - shirt / top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot'], id=None)
+
+def add_target(x:dict):
+  x['target'] = classLabel.int2str(x['label'])
+  return x
+
+learn = load_learner('export.pkl', cpu=True)
+
+def classify(inp):
+  img = PILImageBW.create(inp)
+  item = dict(image=img)
+  pred, _, _ = learn.predict(item)
+  return classLabel.int2str(int(pred))
+
+iface = gr.Interface(
+    fn=classify,
+    inputs=gr.inputs.Image(),
+    outputs="text",
+    title="Fashion Mnist Classifier",
+    description="fastai deployment in Gradio.",
+).launch()