Re-implementation yolov3 in pytorch
Extra dependencies:
Usage
train.py [-h] [--fr] [--pre] [--con] [--cfg CFG] [--ncl NUM_CLASS]
[--sch] --data DATA [--lb LABELS] [--split SPLIT]
[--bs BATCH_SIZE] [--nw NUM_WORKER] [--op {sgd,adam}]
[--mo MOMENTUM] [--lr LR] [--wd WD] [--ep EPOCH] [--cpu]
[--log LOG_PATH] [--lo LB_OBJ] [--lno LB_NOOBJ] [--lpo LB_POS]
[--lcl LB_CLSS]
optional arguments:
-h, --help show this help message and exit
required arguments:
--data DATA path to data folder
--lb LABELS path to labels
optional arguments:
--fr freeze pretrained backbone (True)
--pre use pretrained (False)
--con not continue training
--cfg CFG use custom config, if use, pass the path of custom cfg
file, default is (./config/yolov3.cfg)
--ncl NUM_CLASS number of annot classes (21)
--sch set it to turn on using scheduler (False)
--split SPLIT split ratio [0., 1.] of voc dataset (None) if not None
--bs BATCH_SIZE number of batch size (8)
--nw NUM_WORKER number of worker (0)
--op {sgd,adam} type of optimizer: sgd/adam (sgd)
--mo MOMENTUM Momentum for sgd (0.91)
--lr LR learning rate (0.01)
--wd WD weight decay (1e-4)
--ep EPOCH number of epoch (20)
--cpu use cpu or not (False)
--log LOG_PATH path to save chkpoint and log (./checkpoint)
--lo LB_OBJ lambda objectness lossfunciton (2.0)
--lno LB_NOOBJ lambda objectless lossfunciton (0.5)
--lpo LB_POS lambda position lossfunciton (1.)
--lcl LB_CLSS lambda class lossfunciton (1.)