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How to decode COCO RLE binary mask to image in JavaScript?

This is an example of COCO RLE mask - https://pastebin.com/ZhE2en4C

This is the output of the YOLOv8 validation run, taken from the generated Predictions.json file.

I'm trying to decode the string in JavaScript and render it on the canvas. The encoded string is valid because in python I can do this:

from pycocotools import mask as coco_mask
from PIL import Image

example_prediction = {
    "image_id": "102_jpg",
    "category_id": 0,
    "bbox": [153.106, 281.433, 302.518, 130.737],
    "score": 0.8483,
    "segmentation": {
      "size": [640, 640],
      "counts": "<RLE string here>"
    }
  }

def rle_to_bitmap(rle):
  bitmap = coco_mask.decode(rle)
  return bitmap

def show_bitmap(bitmap):
  img = Image.fromarray(bitmap.astype(np.uint8) * 255, mode='L')
  img.show()
  input("Press Enter to continue...")
  img.close()
    

mask_bitmap = rle_to_bitmap(example_prediction["segmentation"])
show_bitmap(mask_bitmap)

I can see the decoded mask.

Is there a library that can be used to decode the same string in JavaScript and convert it to an Image? I tried digging into the source code of pycocotools but I couldn't.

P粉709307865P粉709307865353 days ago645

reply all(1)I'll reply

  • P粉024986150

    P粉0249861502023-12-08 09:11:58

    You can draw the mask on the canvas and then export the image if needed.

    For actual drawing, you can use two methods:

    1. Decode the RLE into a binary mask (2D matrix or flattened matrix) and draw pixels based on that mask
    2. Draw the mask directly from the RLE string on the virtual canvas, then rotate it 90 degrees and flip it horizontally

    Here are examples of both:

    // Styling and scaling just for demo
    let wrapper = document.createElement("div")
    wrapper.style.cssText = `
      transform-origin: left top;
      transform: scale(8);
    `
    document.body.style.cssText = `
      background-color: #121212;
      margin: 0;
      overflow: hidden;
    `
    document.body.appendChild(wrapper)
    
    // Helpers
    function createCanvas(width, height) {
      let canvas = document.createElement("canvas")
    
      canvas.style.cssText = `
        border: 1px solid white;
        display: block;
        float: left;
        image-rendering: pixelated;
      `
      canvas.height = height
      canvas.width = width
    
      // Comment this line if you need only image sources
      wrapper.appendChild(canvas)
    
      return canvas
    }
    
    function randomColorRGBA() {
      return [
            Math.round(Math.random() * 255),
            Math.round(Math.random() * 255),
            Math.round(Math.random() * 255),
            255
          ]
    }
    
    // Fast array flattening (faster than Array.proto.flat())
    function flatten(arr) {
      const flattened = []
    
      !(function flat(arr) {
        arr.forEach((el) => {
          if (Array.isArray(el)) flat(el)
          else flattened.push(el)
        })
      })(arr)
    
      return flattened
    }
    
    // Decode from RLE to Binary Mask
    // (pass false to flat argument if you need 2d matrix output)
    function decodeCocoRLE([rows, cols], counts, flat = true) {
      let pixelPosition = 0,
          binaryMask
      
      if (flat) {
        binaryMask = Array(rows * cols).fill(0)
      } else {
        binaryMask = Array.from({length: rows}, (_) => Array(cols).fill(0))
      }
    
      for (let i = 0, rleLength = counts.length; i < rleLength; i += 2) {
        let zeros = counts[i],
            ones = counts[i + 1] ?? 0
    
        pixelPosition += zeros 
    
        while (ones > 0) {
          const rowIndex = pixelPosition % rows,
                colIndex = (pixelPosition - rowIndex) / rows
    
          if (flat) {
            const arrayIndex = rowIndex * cols + colIndex
            binaryMask[arrayIndex] = 1
          } else {
            binaryMask[rowIndex][colIndex] = 1
          }
    
          pixelPosition++
          ones--
        }
      }
    
      if (!flat) {
        console.log("Result matrix:")
        binaryMask.forEach((row, i) => console.log(row.join(" "), `- row ${i}`))
      }
    
      return binaryMask
    }
    
    // 1. Draw from binary mask
    function drawFromBinaryMask({size, counts}) {
      let fillColor = randomColorRGBA(),
          height = size[0],
          width = size[1]
    
      let canvas = createCanvas(width, height),
          canvasCtx = canvas.getContext("2d"),
          imgData = canvasCtx.getImageData(0, 0, width, height),
          pixelData = imgData.data
    
      // If you need matrix output (flat = false)
      // let maskFlattened = flatten(decodeCocoRLE(size, counts, false)),
      //     maskLength = maskFlattened.length;
      
      // If not - it's better to use faster approach
      let maskFlattened = decodeCocoRLE(size, counts),
          maskLength = maskFlattened.length;
    
      for(let i = 0; i < maskLength; i++) {
        if (maskFlattened[i] === 1) {
          let pixelPosition = i * 4
    
          pixelData[pixelPosition] = fillColor[0]
          pixelData[pixelPosition + 1] = fillColor[1]
          pixelData[pixelPosition + 2] = fillColor[2]
          pixelData[pixelPosition + 3] = fillColor[3]
        }
      }
    
      canvasCtx.putImageData(imgData, 0, 0)
    
      // If needed you can return data:image/png 
      // to use it as an image.src
      return canvas.toDataURL()
    }
    
    // 2. Draw using virtual canvas
    function drawDirectlyFromRle({size: [rows, cols], counts}) {
      let fillColor = randomColorRGBA(),
          isOnesInterval = false,
          start = 0,
          end = 0
    
      let realCanvas = createCanvas(cols, rows),
          realCtx = realCanvas.getContext("2d")
    
      let virtualCanvas = new OffscreenCanvas(rows, cols),
          virtualCtx = virtualCanvas.getContext("2d"),
          imgData = virtualCtx.getImageData(0, 0, rows, cols),
          pixelData = imgData.data
    
      counts.forEach((interval) => {
        end = start + interval * 4
        if (isOnesInterval) {
          for (let i = start; i < end; i += 4) {
            pixelData[i] = fillColor[0]
            pixelData[i + 1] = fillColor[1]
            pixelData[i + 2] = fillColor[2]
            pixelData[i + 3] = fillColor[3]
          }
        }
        start = end
        isOnesInterval = !isOnesInterval
      })
    
      virtualCtx.putImageData(imgData, 0, 0)
    
      realCtx.save()
      realCtx.scale(-1, 1)
      realCtx.rotate(90*Math.PI/180)
      realCtx.drawImage(virtualCanvas, 0, 0)
      realCtx.restore()
    
      // If needed you can return data:image/png 
      // to use it as an image.src
      return realCanvas.toDataURL()
    }
    
    // Test RLE
    const exampleCocoRLE = {
            counts: [15, 1, 9, 1, 3, 3, 2, 1, 8, 1, 8, 1, 3, 3, 2, 1, 8, 1, 7, 1, 11],
            size: [9, 10]
        }
    
    // Draw on canvas
    let imageSrc1 = drawFromBinaryMask(exampleCocoRLE),
        imageSrc2 = drawDirectlyFromRle(exampleCocoRLE)
    
    console.log("Canvas 1 image (from binary):\n", imageSrc1)
    console.log("Canvas 2 image (from virtual):\n", imageSrc2)
    
    // Example of src usage
    let image1 = document.createElement("img"),
        image2 = document.createElement("img"),
        imageStyle = `
          display: block;
          float: left;
          border: 1px solid lime;
          image-rendering: pixelated;
        `
    
    // demo styling
    image1.style.cssText = imageStyle
    image2.style.cssText = imageStyle
    
    image1.onload = () => {
      wrapper.appendChild(image1)
    }
    image2.onload = () => {
      wrapper.appendChild(image2)
    }
    
    image1.src = imageSrc1
    image2.src = imageSrc2

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