0.2.0
0.2.0
Updates notes
【2022/01/18】
Features
- Saved 30% memory useage in COCO training. #1066
- Log per class AP & AP during evaluation. #1026 #1052
- Users could install yolox from pip now! Supports on more platform is coming. #1020 #1079
- Optimize dynamic matching in label assignment. #861
For pip users
pip install yolox
could help you to install yolox now.
Exp design
YOLOX use Exp
as a controller. With Exp object, users could do everything they want.
e.g.
If you want to get something used in yolox tiny.
from yolox.exp import get_exp
exp = get_exp(exp_name="yolox-tiny") # yolox-tiny could be replaced by yolox-nano/s/m and so on
model = exp.get_model() # now you get yolox-tiny model
dataloader = exp.get_data_loader(batch_size=8, is_distributed=False)
optimizer = exp.get_optimizer(batch_size=2)
Training with pip installed yolox
Since pip will auto install yolox in its own way, users may use a environment variable named YOLOX_DATADIR
.
Check more details from our docs here.