"gradio img classify" Code Answer's
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gradio img classify
Crazy Cottonmouth
on Apr 23, 2021
import gradio as gr
import tensorflow as tf
import numpy as np
import requests
inception_net = tf.keras.applications.InceptionV3() # 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, 299, 299, 3))
inp = tf.keras.applications.inception_v3.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=(299, 299))
label = gr.outputs.Label(num_top_classes=3)
gr.Interface(fn=classify_image, inputs=image, outputs=label, capture_session=True).launch()Source: www.gradio.app
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