Writing own barcode detector any comments really welcome

I am writing my own little network, where I tried to implement the convolution with a kernel that detects edges

import * as tf from "@tensorflow/tfjs-node";


const model = tf.sequential()
// Layer 1: Convolutional
const kArr = [-1, 2, -1, -1, 2, -1, -1, 2, -1,]
const kernel = tf.tensor4d(kArr, [3, 3, 1, 1]).cast("float32").div(6)

model.add(
  tf.layers.conv2d({
    inputShape: [224, 224, 1],
    filters: 1,
    kernelSize: 3,
    padding: "same",
    activation: "relu",
    weights: [kernel],
    trainable: false
  })
)
model.add(
  tf.layers.conv2d({
    inputShape: [224, 224, 1],
    filters: 3,
    kernelSize: 2,
    padding: "same",
    activation: "relu",
  })
);
model.add(tf.layers.flatten())
model.add(tf.layers.dense({ units: 128, activation: "relu" }))
model.add(tf.layers.dense({ units: 64, activation: "relu" }))
model.add(tf.layers.dense({ units: 4, activation: "sigmoid" }))
model.compile({
  optimizer: tf.train.adam(0.00001), //could be a parameter as well.
  loss: tf.losses.meanSquaredError,
});

export { model as simpleModel };

I took the kernel from wikipedia Line detection - Wikipedia