Hi! I am reproducing EagerMOT on KITTI with pointgnn as 3d detection and tracking_best(motsfusion + trackrcnn) as 2d detection for my bachelor degree thesis. But I am quite confusing about the format of the detection results of trackrcnn. In website of MOTS, under downloads there are 3 subtitles. I don't know which dataset should I use and their format. Could you please help me understand their format? Or can you give the source of format they use?
I download the files from Detection for Tracking Oly Challenge, and unzip MOTS20_detections.zip. There is a folder named KITTI_MOTS in it. And I use this as input, but I can not understand the input format. The txt format mentioned in https://www.vision.rwth-aachen.de/page/mots consisted of 6 parts for each line. But in each line in the txt I downloaded there are more than 10 items as follows:
I tried to compare the format with your code in input/detections_ed.py parse_trackrcnn_seg() function as follows.
def parse_trackrcnn_seg(seg_values):
""" Returns class, score, mask, bbox and reid parsed from input """
mask = {'size': [int(seg_values[7]), int(seg_values[8])],
'counts': seg_values[9].strip().encode(encoding='UTF-8')}
box = (int(float(seg_values[1])), int(float(seg_values[2])),
int(float(seg_values[3])), int(float(seg_values[4])))
return (int(seg_values[6]), float(seg_values[5]), mask, box, [float(e) for e in seg_values[10:]])
I guess some idems in file mean classes, scores, masks, boxes and reids. In MOTS website, the annotation mentioned run-length encoding but in this function, the rle(10th item, very long string) is assigned to mask['counts']. I don't understand what does this variable mean. Website say rle is related to cocotool. But I didn't find anything related to this mask['counts'] value and cocotool in the repo.
The txt downloaded from under MOTSChallenge seems like
Hi! I am reproducing EagerMOT on KITTI with pointgnn as 3d detection and tracking_best(motsfusion + trackrcnn) as 2d detection for my bachelor degree thesis. But I am quite confusing about the format of the detection results of trackrcnn. In website of MOTS, under downloads there are 3 subtitles. I don't know which dataset should I use and their format. Could you please help me understand their format? Or can you give the source of format they use?
I download the files from Detection for Tracking Oly Challenge, and unzip MOTS20_detections.zip. There is a folder named KITTI_MOTS in it. And I use this as input, but I can not understand the input format. The txt format mentioned in https://www.vision.rwth-aachen.de/page/mots consisted of 6 parts for each line. But in each line in the txt I downloaded there are more than 10 items as follows:
I tried to compare the format with your code in input/detections_ed.py parse_trackrcnn_seg() function as follows.
I guess some idems in file mean classes, scores, masks, boxes and reids. In MOTS website, the annotation mentioned run-length encoding but in this function, the rle(10th item, very long string) is assigned to mask['counts']. I don't understand what does this variable mean. Website say rle is related to cocotool. But I didn't find anything related to this mask['counts'] value and cocotool in the repo.
The txt downloaded from under MOTSChallenge seems like
what is the number after rle( run-length encoding) mean? Do they mean reid?
I am new to object tracking field so the question above is probably basic. I will appreciate it if you give some kind help.