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:
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