Evaluation time on transfer learning
bbln33 opened this issue · comments
Dear author,
Thanks for nice works!
I have a question of the inference time on transfer learning.
As you described in README, I run the evaluate script below:
python3 ./tools/train_net.py \
--eval-only \
--num-gpus 8 \
--config-file ./configs/COCO-InstanceSegmentation/CLIP_fast_rcnn_R_50_C4_ovd.yaml \
MODEL.WEIGHTS ./pretrained_ckpt/regionclip/regionclip_finetuned-coco_rn50.pth \
MODEL.CLIP.OFFLINE_RPN_CONFIG ./configs/COCO-InstanceSegmentation/mask_rcnn_R_50_C4_1x_ovd_FSD.yaml \
MODEL.CLIP.BB_RPN_WEIGHTS ./pretrained_ckpt/rpn/rpn_coco_48.pth \
MODEL.CLIP.TEXT_EMB_PATH ./pretrained_ckpt/concept_emb/coco_48_base_cls_emb.pth \
MODEL.CLIP.OPENSET_TEST_TEXT_EMB_PATH ./pretrained_ckpt/concept_emb/coco_65_cls_emb.pth \
MODEL.ROI_HEADS.SOFT_NMS_ENABLED True \
I use NVIDIA 3090 8 gpus, but I guess it is little bit too long for evaluation.
Is is possible to share the inference time on transfer learning?
Hi!
Thanks for this great work!
However,I face the same thing. When I inference on a V100, it takes 10 seconds to infer 1 image. Is that normal?
OKAY I have found my mistake, bad weight loading. FYI, mine is 1s/ iter.
Hey @bbln33, I met the same problem. It takes me ~1 hour on COCO validation, but a standard mask-rcnn provided by detectron2 only takes minutes. Did you solve it? Could you provide us how long it takes with your environment?
In my case, the whole inference time is around 4 hours. I found that it depends on the MODEL.ROI_HEADS.SOFT_NMS_ENABLED
option. When it sets true
, it takes more time than false
.