diff --git a/observe_bact.html b/observe_bact.html
index 08f280a..4f820bb 100644
--- a/observe_bact.html
+++ b/observe_bact.html
@@ -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]]);
             }
           }