Row 2255

Row ID: 2255 | Dataset Entry | Axioma AXP Content Repository

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Crosspost from my stackoverflow. I would put it on the tfjs sub but it is tiny.

I am sure the solution is out there somewhere, but I have been unable to find it. I originally trained the model in normal tensorflow, but it is being used in tensorflowjs after being converted. My current error is

>Uncaught (in promise) Error: Size(30000) must match the product of shape 100,100,3

Though I have had many others through my attempts.

My code right now is

function preprocess(imageData) { //const img_arr = cv.imread(imageData); let inputTensor = tf.browser.fromPixels(imageData); const offset = tf.scalar(255.0); const normalized = tf.scalar(1.0).sub(inputTensor.div(offset)); const batchInputShape = [100, 100, 3]; const flattenedInput = tf.reshape(normalized, [batchInputShape]); console.log(flattenedInput.shape); return flattenedInput;

The result of this function is then fed into my model, which produces the error. I am sure the solution is obvious but I have been unable to find it.

I have also tried

const batchInputShape = [null, 100, 100, 3]; const flattenedInput = tf.reshape(normalized, [batchInputShape, -1]);

Though that did not fair any better.

FieldValue
text Crosspost from my stackoverflow. I would put it on the tfjs sub but it is tiny. I am sure the solution is out there somewhere, but I have been unable to find it. I originally trained the model in normal tensorflow, but it is being used in tensorflowjs after being converted. My current error is >Uncaught (in promise) Error: Size(30000) must match the product of shape 100,100,3 Though I have had many others through my attempts. My code right now is function preprocess(imageData) { …
label r/tensorflow
dataType post
communityName r/tensorflow
datetime 2023-07-27
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url_encoded Z0FBQUFBQm5Lak9FOHJaSVdwUUNjeE4wRnJ1dG9kbTI0QjQ1SllabHlCUlVjSVhHU01FSzlaZ0kyM1I3c2RFU29rVGRFUDk2aXBoZEozTEFYaHZYX1E5ZVNnVlBXZy1WUXRRaXRSZnlVMWdKWWFTLVFXbFlNMnU0cGQ2V0VtUFNTY1ZlUG1HMnpWaU5uNU5CbS1oSnJfcEZ0Q251N0NydDUybjVVMi1WbVN3WWVnZFB1WGFMR21WWHg4MnJLeHplVVBHbjViRTNqSWpHNmprZnlYekVIZmp1MHVlTWZvX0hxZz09

Raw Record

{
  "text": " Crosspost from my stackoverflow. I would put it on the tfjs sub but it is tiny.\n\nI am sure the solution is out there somewhere, but I have been unable to find it. I originally trained the model in normal tensorflow, but it is being used in tensorflowjs after being converted. My current error is\n\n>Uncaught (in promise) Error: Size(30000) must match the product of shape 100,100,3  \n \n\nThough I have had many others through my attempts.\n\nMy code right now is\n\n    function preprocess(imageData) {     //const img_arr = cv.imread(imageData); let inputTensor = tf.browser.fromPixels(imageData);     const offset = tf.scalar(255.0);     const normalized = tf.scalar(1.0).sub(inputTensor.div(offset));     const batchInputShape = [100, 100, 3];     const flattenedInput = tf.reshape(normalized, [batchInputShape]);     console.log(flattenedInput.shape);     return flattenedInput; \n\nThe result of this function is then fed into my model, which produces  the error. I am sure the solution is obvious but I have been unable to  find it.\n\nI have also tried\n\n    const batchInputShape = [null, 100, 100, 3]; const flattenedInput = tf.reshape(normalized, [batchInputShape, -1]); \n\nThough that did not fair any better.",
  "label": "r/tensorflow",
  "dataType": "post",
  "communityName": "r/tensorflow",
  "datetime": "2023-07-27",
  "username_encoded": "Z0FBQUFBQm5LakwweFNkcEdBZHFlbWZ3NmQtYmc2VUk2NXBrc2Yxdk1aSjU4M09mZDQ2dmtaeUhsdzVVM1lUSVdyRFNhVVFNa283aXhXaG9hOUNuVXVmQk1lWFo1Vy15TGc9PQ==",
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}
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