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.
:::python3

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](https://github.com/Megvii-BaseDetection/YOLOX/tree/main/datasets).