Business
Jobs
  • About Us
  • Solutions
    • Job Postings
      Post your job and receive qualified candidates in 48h.
    • Candidate Assessments
      500+ technical and psychological tests, plus anti-fraud.
    • Headhunting
      Tailor-made executive search from start to finish.
    • Payroll + EOR
      Payroll dispersal and EOR across 15+ LATAM countries.
  • Pricing
  • Jobs

0

444
Views
Uncaught (in promise) Error: Failed to compile fragment shader

So I'm using tensorflow JS and python for training models. Now I'm working on the website so that abstract doctors could upload an MRI image and get the prediction. Here's my code:

<script>
    async function LoadModels(){  
               model = undefined;
               model = await tf.loadLayersModel("http://127.0.0.1:5500/modelsBrain/modelBrain.json");
               const image = document.getElementById("image");
               const image1 = tf.browser.fromPixels(image);
               const image2 = tf.reshape(image1, [1,200,200,3]);
               const prediction = model.predict(image2);
               const softmaxPred = prediction.softmax().dataSync();
               alert(softmaxPred);

               let top5 = Array.from(softmaxPred)
                    .map(function (p, i) {
                        return {
                            probability: p,
                            className: TARGET_CLASSES_BRAIN[i]
                        };
                    }).sort(function (a, b) {
                        return b.probability - a.probability;
                    }).slice(0, 4);
                    
            const pred = [[]];
            top5.forEach(function (p) {
            pred.push(p.className, p.probability);
            alert(p.className + ' ' + p.probability);
        });
            }

    const fileInput = document.getElementById("file-input");
    const image = document.getElementById("image");

    function getImage() {
        if(!fileInput.files[0])
        throw new Error("Image not found");
        const file = fileInput.files[0];

        const reader = new FileReader();

        reader.onload = function (event) {
            const dataUrl = event.target.result;
            const imageElement = new Image();
            imageElement.src = dataUrl;

            imageElement.onload = async function () {
                image.setAttribute("src", this.src);
                image.setAttribute("height", this.height);
                image.setAttribute("width", this.width);
                await LoadModels();
            };
        };

        reader.readAsDataURL(file);
    }
    fileInput.addEventListener("change", getImage);
</script>

This error occurrs not every (!) Live Server open. I am confused, what seems to be the problem?

enter image description here

about 4 years ago · Juan Pablo Isaza
1 answers
Answer question

0

Error CONTEXT_LOST_WEBGL is 99% due to low GPU memory - what kind of HW do you have available? Alternatively, you can try WASM backend which runs computation on CPU and doesn't require GPU resources.

Btw, you're not deallocating your tensors anywhere so if you're running this in a loop for multiple inputs, you do have a massive memory leak. But if error occurs on the first input already, your GPU simply is not good enough for this model.

about 4 years ago · Juan Pablo Isaza Report
Answer question
Find remote jobs

Discover the new way to find a job!

Top jobs
Top job categories
Business
Post vacancy Pricing Sales
Legal
Terms and conditions Privacy policy
© 2026 PeakU Inc. All Rights Reserved.
Andres GPT
Show me some job opportunities
There's an error!