问图像调整方法(resizeBilinear和resizeNearestNeighbor)在Tensorflow.js中不返回正确的结果。
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Stack Overflow用户

提问于 2020-09-17 11:33:33

回答 1查看 1.5K关注 0票数 3

问题

resizeBilinear(*1)和resizeNearestNeighbor(*2)有什么区别？特别是，resizeNearestNeighbor没有返回正确的图像(一半图像是黑色的)。(图像的一半是黑色的。)
ResizeBilinear不返回分割的正确结果。(图像的一半是灰色的。)为什么会这样呢？这与resizeNearestNeighbor的结果非常相似。

背景

我想开发一个在Tensorflow.js中进行分段的应用程序。幸运的是，我在Python中找到了一些用于分段的示例代码。(*3)我相信我可以通过将获得的Keras模型转换为TFJS模型，在Tensorflow.js中进行分段。我试图调整Tensorflow.js中的图像大小，但是我无法得到正确的结果。有人有什么好主意吗？

码

这是我写的源代码。(我不习惯写JavaScript。)

<!DOCTYPE html>
<html>
<head></head>
<meta charset="utf-8"/>
<body>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"></script>
<canvas id="canvas1" width="256" height="256" style="border: 2px solid;"></canvas>
<canvas id='canvas2' width="128" height="128" style="border: 2px solid;"></canvas>
<canvas id='canvas3' width="128" height="128" style="border: 2px solid;"></canvas>
<canvas id='canvas4' width="128" height="128" style="border: 2px solid;"></canvas>
<canvas id='canvas5' width="128" height="128" style="border: 2px solid;"></canvas>
<script>

var inputImg = new Image();inputImg.src = "../00_resources/woman172.jpg";
const canvas1 = document.getElementById('canvas1');
const canvas2 = document.getElementById('canvas2');
const canvas3 = document.getElementById('canvas3');
const canvas4 = document.getElementById('canvas4');
const canvas5 = document.getElementById('canvas5');

const SIZE = 128;
const COL_CHANNEL = 3;
const BIN_CHANNEL = 1;

inputImg.onload = () => {
  const inCtx = canvas1.getContext('2d');
  inCtx.drawImage(inputImg, 0, 0, canvas1.width, canvas1.height);
};


(async() => {

    // load model
    let model = await tf.loadGraphModel('/tfjsdoc/Portrait-Segmentation/model/deconv_bnoptimized_munet_to_tfjs_graph_model/model.json');

    // image1 (original image)
    let img1 = tf.browser.fromPixels(canvas1, COL_CHANNEL);
    tf.browser.toPixels(img1, canvas2);// OK

    // image2 (resized image - using 'resizeNearestNeighbor')
    let img2 = img1.resizeNearestNeighbor([SIZE, SIZE]).toFloat().div(tf.scalar(255));
    tf.browser.toPixels(img2, canvas3);// NG

    // image3 (resized image - using 'resizeBilinear')
    let img3 = img1.resizeBilinear([SIZE, SIZE]).toFloat().div(tf.scalar(255));
    tf.browser.toPixels(img3, canvas4);// OK?

    // predict (image3 is used to make predictions, but the same problem occurs as in image2)
    let pred = await model.predict(tf.reshape(img3, [-1,SIZE,SIZE,COL_CHANNEL])).data();
    tf.browser.toPixels(tf.tensor(pred, [SIZE,SIZE, BIN_CHANNEL]), canvas5);// NG

})();

</script>
</body>
</html>

捕获执行结果

从左到右。