e26182e6ec
Summary: change warmup way by iter not by epoch, which will make it more flexible when training small epochs
1.5 KiB
Getting Started with Fastreid
Prepare pretrained model
If you use backbones supported by fastreid, you do not need to do anything. It will automatically download the pre-train models.
But if your network is not connected, you can download pre-train models manually and put it in ~/.cache/torch/checkpoints.
If you want to use other pre-train models, such as MoCo pre-train, you can download by yourself and set the pre-train model path in configs/Base-bagtricks.yml.
Compile with cython to accelerate evalution
cd fastreid/evaluation/rank_cylib; make all
Training & Evaluation in Command Line
We provide a script in "tools/train_net.py", that is made to train all the configs provided in fastreid. You may want to use it as a reference to write your own training script.
To train a model with "train_net.py", first setup up the corresponding datasets following datasets/README.md, then run:
./tools/train_net.py --config-file ./configs/Market1501/bagtricks_R50.yml MODEL.DEVICE "cuda:0"
The configs are made for 1-GPU training.
If you want to train model with 4 GPUs, you can run:
python tools/train_net.py --config-file ./configs/Market1501/bagtricks_R50.yml --num-gpus 4
To evaluate a model's performance, use
python tools/train_net.py --config-file ./configs/Market1501/bagtricks_R50.yml --eval-only \
MODEL.WEIGHTS /path/to/checkpoint_file MODEL.DEVICE "cuda:0"
For more options, see ./tools/train_net.py -h.