Opencv.js via npm for blob-detection (#1185)

This commit is contained in:
aashna27
2019-08-02 19:26:03 +05:30
committed by Jeffrey Warren
parent 4dfdccada9
commit 68d5db7cff
8 changed files with 152 additions and 0 deletions

View File

@@ -9,6 +9,7 @@ List of Module Documentations
4. [Add QR](#Add-QR-module)
5. [Average](#average-module)
6. [Blend](#blend-module)
7. [Blob-Analysis](#blob-analysis)
7. [Blur](#blur-module)
8. [Brightness](#brightness-module)
9. [Channel](#channel-module)
@@ -155,6 +156,20 @@ where `options` is an object with the following properties:
* offset: step of image with which current image is to be blended(Two steps back is -2, three steps back is -3 etc; default -2)
* func: function used to blend two images (default : function(r1, g1, b1, a1, r2, g2, b2, a2) { return [ r1, g2, b2, a2 ] })
## Blob Analysis
This module uses Opencv.js for detecting and marking blob/region in microscopic images. It requires an opencv.js file to
be loaded before using the functionalities which is currently being loaded to the webpage via script.It supports both environments, Node.js and browser for processing.
As the size of opencv.js file is quite large, the future versions will focus on loading it asynchronously, on demand of the the module to optimise performance.
#### Usage
```js
sequencer.loadImage('PATH')
.addSteps('blob-analysis')
.run()
```
## blur-module
This module is used for applying a Gaussian blur effect.

View File

@@ -232,6 +232,7 @@
var sequencer;
})
</script>
<script async src="../node_modules/opencv.js/opencv.js" type="text/javascript"></script>
</body>

View File

@@ -60,6 +60,7 @@
"jsqr": "^1.1.1",
"lodash": "^4.17.11",
"ndarray": "^1.0.18",
"opencv.js": "^1.2.1",
"ora": "^3.0.0",
"pace": "0.0.4",
"puppeteer": "^1.14.0",

View File

@@ -5,6 +5,7 @@ module.exports = {
'add-qr': require('./modules/AddQR'),
'average': require('./modules/Average'),
'blend': require('./modules/Blend'),
'blob-analysis': require('./modules/BlobAnalysis'),
'blur': require('./modules/Blur'),
'brightness': require('./modules/Brightness'),
'canvas-resize': require('./modules/CanvasResize'),

View File

@@ -0,0 +1,81 @@
module.exports = function(pixels, options, priorStep){
var $ = require('jquery'); // to make Blob-analysis work for node.js
var img = $(priorStep.imgElement);
if(Object.keys(img).length === 0){
img = $(priorStep.options.step.imgElement);
}
var canvas = document.createElement('canvas');
canvas.width = pixels.shape[0];
canvas.height = pixels.shape[1];
var ctx = canvas.getContext('2d');
ctx.drawImage(img[0], 0, 0);
let imgData = ctx.getImageData(0, 0, canvas.width, canvas.height);
let src = cv.matFromImageData(imgData);
let dst = new cv.Mat();
let gray = new cv.Mat();
let opening = new cv.Mat();
let imageBg = new cv.Mat();
let imageFg = new cv.Mat();
let distTrans = new cv.Mat();
let unknown = new cv.Mat();
let markers = new cv.Mat();
// gray and threshold image
cv.cvtColor(src, gray, cv.COLOR_RGBA2GRAY, 0);
cv.threshold(gray, gray, 0, 255, cv.THRESH_BINARY_INV + cv.THRESH_OTSU);
// get background
let M = cv.Mat.ones(3, 3, cv.CV_8U);
cv.erode(gray, gray, M);
cv.dilate(gray, opening, M);
cv.dilate(opening, imageBg, M, new cv.Point(-1, -1), 3);
// distance transform
cv.distanceTransform(opening, distTrans, cv.DIST_L2, 5);
cv.normalize(distTrans, distTrans, 1, 0, cv.NORM_INF);
// get foreground
cv.threshold(distTrans, imageFg, 0.7 * 1, 255, cv.THRESH_BINARY);
imageFg.convertTo(imageFg, cv.CV_8U, 1, 0);
cv.subtract(imageBg, imageFg, unknown);
// get connected components markers
cv.connectedComponents(imageFg, markers);
for (let i = 0; i < markers.rows; i++) {
for (let j = 0; j < markers.cols; j++) {
markers.intPtr(i, j)[0] = markers.ucharPtr(i, j)[0] + 1;
if (unknown.ucharPtr(i, j)[0] == 255) {
markers.intPtr(i, j)[0] = 0;
}
}
}
cv.cvtColor(src, src, cv.COLOR_RGBA2RGB, 0);
cv.watershed(src, markers);
// draw barriers
for (let i = 0; i < markers.rows; i++) {
for (let j = 0; j < markers.cols; j++) {
if (markers.intPtr(i, j)[0] == -1) {
src.ucharPtr(i, j)[0] = 255; // R
src.ucharPtr(i, j)[1] = 0; // G
src.ucharPtr(i, j)[2] = 0; // B
}
}
}
cv.imshow(canvas, src);
src.delete(); dst.delete(); gray.delete(); opening.delete(); imageBg.delete();
imageFg.delete(); distTrans.delete(); unknown.delete(); markers.delete(); M.delete();
var myImageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
pixels.data = myImageData.data;
return pixels;
};

View File

@@ -0,0 +1,43 @@
module.exports = function BlobAnalysis(options, UI){
var output;
function draw(input, callback, progressObj) {
progressObj.stop(true);
progressObj.overrideFlag = true;
var step = this;
var priorStep = this.getStep(-1); // get the previous step to process it
function extraManipulation(pixels){
pixels = require('./BlobAnalysis')(pixels, options, priorStep);
return pixels;
}
function output(image, datauri, mimetype){
step.output = { src: datauri, format: mimetype};
}
return require('../_nomodule/PixelManipulation.js')(input, {
output: output,
extraManipulation: extraManipulation,
format: input.format,
image: options.image,
inBrowser: options.inBrowser,
callback: callback
});
}
return {
options: options,
draw: draw,
output: output,
UI: UI
};
};

View File

@@ -0,0 +1,4 @@
module.exports = [
require('./Module'),
require('./info.json')
];

View File

@@ -0,0 +1,6 @@
{
"name": "Blob Analysis",
"description": "Blob/Region identification for microscopic images.",
"inputs": {},
"docs-link":"https://github.com/publiclab/image-sequencer/blob/main/docs/MODULES.md#blob-analysis"
}