File size: 947 Bytes
2721128 45d3c14 2721128 f268a7f 2721128 5707875 2721128 f268a7f 51a4155 2721128 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | import requests
import tensorflow as tf # type: ignore
import gradio as gr
# get_image() returns the file path to sample images included with Gradio
from gradio.media import get_image
inception_net = tf.keras.applications.MobileNetV2() # load the model
# Download human-readable labels for ImageNet.
response = requests.get("https://git.io/JJkYN")
labels = response.text.split("\n")
def classify_image(inp):
inp = inp.reshape((-1, 224, 224, 3))
inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp)
prediction = inception_net.predict(inp).flatten()
return {labels[i]: float(prediction[i]) for i in range(1000)}
image = gr.Image()
label = gr.Label(num_top_classes=3)
demo = gr.Interface(
fn=classify_image,
inputs=image,
outputs=label,
examples=[
get_image("cheetah1.jpg"),
get_image("lion.jpg")
],
api_name="predict"
)
if __name__ == "__main__":
demo.launch()
|