annotations files not complete?
FightForCS opened this issue · comments
Hi, I want to evalute your pretrained model. I download "minival annotation" file and "Person detection results in COCO Minival" file from your link, but it seems that some images are missing. Here are my test codes:
val = json.load(open('./MSCOCO/annotations/person_keypoints_minival2014.json', 'r'))
train = json.load(open('./MSCOCO/annotations/person_keypoints_trainvalminusminival2014.json', 'r'))
det = json.load(open('./dets/person_detection_minival411_human553.json', 'r'))
det_image_ids = set([i['image_id'] for i in det])
val_image_ids = set([i['id'] for i in val['images']])
val_annot_ids = set([i['id'] for i in val['annotations']])
val_annot_img_ids = set([i['image_id'] for i in val['annotations']])
print(len(val_image_ids & val_annot_img_ids))
print(len(det_image_ids & val_annot_img_ids))
output is
2693
2692
it seems that many annotatated images(ground truth) do not exist in your detection result file and your minival. What is the reason? Thanks.
There is no person in the rest of images. COCO minival dataset has 5000 images, which includes about 2000+ images with persons.
@chenyilun95 Thanks for your qucik reply, then why there are 4581 unique images containing person in your 'person_detection_minival411_human553.json' file? Is it becasue you have not apply NMS to the final detection results?
Softnms has been applied in the detection result. We filter images whose person score is very low.
I see, so, we only need to filter low score person and run pretrained CPN on those filtered images?
It’s OK. You should use nms to filter the detection boxes anyway. The code is without nms by default.
thx