mnist

.gitignore

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+.idea/*

app.py

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+import tensorflow as tf
+import numpy as np
+from urllib.request import urlretrieve
+import gradio as gr
+
+urlretrieve("https://gr-models.s3-us-west-2.amazonaws.com/mnist-model.h5", "mnist-model.h5")
+model = tf.keras.models.load_model("mnist-model.h5")
+
+def recognize_digit(image):
+    image = image.reshape(1, -1)  # add a batch dimension
+    prediction = model.predict(image).tolist()[0]
+    return {str(i): prediction[i] for i in range(10)}
+
+gr.Interface(fn=recognize_digit, 
+             inputs="sketchpad", 
+             outputs=gr.outputs.Label(num_top_classes=3),
+             live=True,
+             css=".footer{display:none}",
+             # title="MNIST Sketchpad",
+             description="Draw a number 0 through 9 on the sketchpad, and click submit to see the prediction. Model trained on the MNIST dataset.",
+             thumbnail="https://raw.githubusercontent.com/gradio-app/real-time-mnist/master/thumbnail2.png").launch();

models/mnist-99.0-acc.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:96db0bab1f1fcaa5c9bfc4821c041db55713eb4c594d738294ee7eb9ccfe75ad
+size 4997568

requirements.txt

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+tensorflow==2.3.0
+gradio>=2.2.6