mirror of
https://github.com/gradio-app/gradio.git
synced 2024-12-21 02:19:59 +08:00
38 lines
770 B
Python
38 lines
770 B
Python
import os
|
|
from urllib.request import urlretrieve
|
|
|
|
import tensorflow as tf
|
|
|
|
import gradio
|
|
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)
|
|
prediction = model.predict(image).tolist()[0]
|
|
return {str(i): prediction[i] for i in range(10)}
|
|
|
|
|
|
im = gradio.inputs.Image(
|
|
shape=(28, 28), image_mode="L", invert_colors=False, source="canvas"
|
|
)
|
|
|
|
iface = gr.Interface(
|
|
recognize_digit,
|
|
im,
|
|
gradio.outputs.Label(num_top_classes=3),
|
|
live=True,
|
|
interpretation="default",
|
|
capture_session=True,
|
|
)
|
|
|
|
iface.test_launch()
|
|
|
|
if __name__ == "__main__":
|
|
iface.launch()
|