himbeere/open-organism-observer
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add image cropping

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lukas fricke 2025-02-05 14:07:15 +01:00
parent 0bf4fd2285
commit 0d09bb5e96
1 changed files with 36 additions and 8 deletions
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observe_bact.html
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@ -680,6 +680,9 @@
var cap = new cv.VideoCapture(video);
let src = new cv.Mat(video.offsetHeight, video.offsetWidth, cv.CV_8UC4);
let dst = new cv.Mat(video.offsetHeight, video.offsetWidth, cv.CV_8UC1);
let draw = new cv.Mat(video.offsetHeight, video.offsetWidth, cv.CV_8UC4);
var rects_old_frame = [];
var objects_last = [];
let contours = new cv.MatVector();
@ -692,16 +695,21 @@
function processVideo() {
cap.read(src);
cap.read(draw);
framecount+=1;
let objects_this = [];
let fits = [];
let rects = [];
let areas = [];
let cropped_image = [];
try {
if (!streaming) {
// clean and stop.
src.delete();
dst.delete();
draw.delete();
return;
}
@ -719,23 +727,42 @@
if (cv.contourArea(cnt) < 1000){
continue;
}
// get the bounding rect of the contour
let rect = cv.boundingRect(cnt);
//let rect = cv.minAreaRect(cnt)
let cropped_ref = src.roi(rect);
// prepare an array for fitnes values
rects.push(rect);
let sample = new cv.Mat(rect.height, rect.width, cv.CV_8UC4);
cropped_ref.copyTo(sample);
cropped_image.push(sample);
let area = cv.contourArea(cnt);
let s = src.size();
s = microscope_setup.FoV_Width / s.width;
areas.push(area*Math.pow(s,2));
let rectangleColor = new cv.Scalar(255, 0, 255,255);
let point1 = new cv.Point(rect.x, rect.y);
let point2 = new cv.Point(rect.x + rect.width, rect.y + rect.height);
cv.rectangle(src, point1, point2, rectangleColor, 2, cv.LINE_AA, 0);
// get all fitness values for this rect.
//box = cv.boxPoints(rect);
//box = np.int0(box);
cv.rectangle(draw, point1, point2, rectangleColor, 2, cv.LINE_AA, 0);
//cv.drawContours(draw,[box],0,rectangleColor,2);
//console.log(rect);
// get all fitness values for this rect. first for already tracked rects
for (let k = 0; k < objects_tracked.length; ++k){
if (objects_tracked[k].at(-1)[0] == framecount-1){
fits.push([k, 'NaN', rects.length-1, fit(objects_tracked[k].at(-1)[1], rect)]);
}
}
// get all fitness values for rects that have not been tracked.
for (let j = 0; j < objects_last.length; ++j){
fits.push(['NaN', j, rects.length-1, fit(objects_last[j], rect)]);
fits.push(['NaN', j, rects.length-1, fit(objects_last[j][1], rect)]);
}
}
// sort fits array
@ -756,12 +783,12 @@
break;
}
else if (ind_new == 'NaN' && !(objects_tracked_handled.has(ind_tracked)) && !(rects_handled.has(ind_rect))){
objects_tracked[ind_tracked].push([framecount, rects[ind_rect]]);
objects_tracked[ind_tracked].push([framecount, rects[ind_rect], cropped_image[ind_rect], areas[ind_rect]]);
objects_tracked_handled.add(ind_tracked);
rects_handled.add(ind_rect);
let rectangleColor = new cv.Scalar(255, 0, 255,255);
point1 = new cv.Point(rects[ind_rect].x, rects[ind_rect].y);
cv.putText(src, String(ind_tracked+objects_lost.length), point1, cv.FONT_HERSHEY_COMPLEX, 1, rectangleColor, 1, cv.LINE_8);
cv.putText(draw, String(ind_tracked), point1, cv.FONT_HERSHEY_COMPLEX, 1, rectangleColor, 1, cv.LINE_8);
}
}
@ -776,14 +803,15 @@
break;
}
else if (ind_tracked == 'NaN' && !(objects_new_handled.has(ind_new)) && !(rects_handled.has(ind_rect))){
objects_tracked.push([[framecount-1, objects_last[ind_new]], [framecount, rects[ind_rect]]]);
objects_tracked.push([objects_last[ind_new], [framecount, rects[ind_rect], cropped_image[ind_rect], areas[ind_rect]]]);
add_organism_candidate(objects_last[ind_new], objects_tracked.length);
objects_new_handled.add(ind_new);
rects_handled.add(ind_rect);
}
}
for (let i = 0; i < rects.length; ++i){
if (!(rects_handled.has(i))) {
objects_this.push(rects[i]);
objects_this.push([framecount, rects[i], cropped_image[i], areas[i]]);
}
}