如何使用PHP进行图像识别？

$ sudo apt-get install php-gd
$ sudo service apache2 restart

<?php
header('Content-type: image/jpeg');

$filename = 'example.jpg';

list($width, $height) = getimagesize($filename);
$ration = $width / $height;

$newWidth = 200;
$newHeight = (int) ($newWidth / $ration);

$thumb = imagecreatetruecolor($newWidth, $newHeight);
$source = imagecreatefromjpeg($filename);

imagecopyresampled($thumb, $source, 0, 0, 0, 0, $newWidth, $newHeight, $width, $height);

imagejpeg($thumb);
imagedestroy($thumb);
imagedestroy($source);
?>

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import numpy as np

(train_images, train_labels), (test_images, test_labels) = keras.datasets.mnist.load_data()

train_images = train_images.reshape((60000, 28, 28, 1))
test_images = test_images.reshape((10000, 28, 28, 1))

train_images, test_images = train_images / 255.0, test_images / 255.0

model = keras.Sequential([
    keras.layers.Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)),
    keras.layers.MaxPooling2D((2, 2)),
    keras.layers.Flatten(),
    keras.layers.Dense(10, activation='softmax')
])

model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.fit(train_images, train_labels, epochs=5)

test_loss, test_acc = model.evaluate(test_images, test_labels, verbose=2)
print('
Test accuracy:', test_acc)

image_path = 'test_image.png'
img = keras.preprocessing.image.load_img(image_path, target_size=(28, 28), color_mode="grayscale")
img_array = keras.preprocessing.image.img_to_array(img)
img_array = np.expand_dims(img_array, axis=0)

predictions = model.predict(img_array)
print(predictions)

<?php
$command = escapeshellcmd('python3 path/to/python_script.py');
$output = shell_exec($command);
echo $output;
?>