This directory provides partial configuration implemented by detectron2. Please follow the installation of CenterNet2 to reproduce all results.
Pre-training
To pre-train a CenterNet2 with ResNet-50 backbone on BigDetection using 8 GPUs, run:
python projects/CenterNet2/train_net.py \
--config-file projects/CenterNet2/configs/centernet2_R_50_BigDet_8x.yaml
--num-gpus 8
Data efficiency
To fine-tune a BigDetection pre-trained Faster R-CNN on partial COCO, run:
# 1% COCO
python projects/CenterNet2/train_net.py \
--config-file projects/CenterNet2/configs/faster_rcnn_R_50_FPN_COCO-1.yaml
--num-gpus 8
MODEL.WEIGHTS /path/to/bigdet_pretrained_rcnn_checkpoint
# 2% COCO
python projects/CenterNet2/train_net.py \
--config-file projects/CenterNet2/configs/faster_rcnn_R_50_FPN_COCO-2.yaml
--num-gpus 8
MODEL.WEIGHTS /path/to/bigdet_pretrained_rcnn_checkpoint
# 5% COCO
python projects/CenterNet2/train_net.py \
--config-file projects/CenterNet2/configs/faster_rcnn_R_50_FPN_COCO-5.yaml
--num-gpus 8
MODEL.WEIGHTS /path/to/bigdet_pretrained_rcnn_checkpoint
# 10% COCO
python projects/CenterNet2/train_net.py \
--config-file projects/CenterNet2/configs/faster_rcnn_R_50_FPN_COCO-10.yaml
--num-gpus 8
MODEL.WEIGHTS /path/to/bigdet_pretrained_rcnn_checkpoint