gradio/demo/image_classifier_interpretation/run.py
aliabid94 b4d9825409
Website: WIP (#328)
Ported gradio website into gradio repository, now launched as a docker service from gradio/website
2021-12-13 22:02:19 -08:00

20 lines
690 B
Python

import gradio as gr
import tensorflow as tf
import requests
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.inputs.Image(shape=(224, 224))
label = gr.outputs.Label(num_top_classes=3)
gr.Interface(fn=classify_image, inputs=image, outputs=label, interpretation="default").launch()