我使用此Python代码将给定图像路径转换为新的Tensor。如何在TensorFlow JS中使用Node.js进行相同操作?
def process_image(image_path):
# Read in image file
image = tf.io.read_file(image_path)
# Turn the jpeg image into numerical Tensor with 3 colour channels (Red, Green, Blue)
image = tf.image.decode_jpeg(image, channels=3)
# Convert the colour channel values from 0-225 values to 0-1 values
image = tf.image.convert_image_dtype(image, tf.float32)
# Resize the image to our desired size (224, 244)
image = tf.image.resize(image, size=[IMG_SIZE, IMG_SIZE])
return image
答案 0 :(得分:1)
下面是一个js函数,它将执行与python中相同的处理
const tfnode = require('@tensorflow/tfjs-node')
function processImage(path) {
const imageSize = 224
const imageBuffer = fs.readFileSync(path); // can also use the async readFile instead
// get tensor out of the buffer
image = tfnode.node.decodeImage(imageBuffer, 3);
// dtype to float
image = image.cast('float32').div(255);
// resize the image
image = tf.image.resizeBilinear(image, size = [imageSize, imageSize]); // can also use tf.image.resizeNearestNeighbor
image = image.expandDims(); // to add the most left axis of size 1
return image.shape
}