lizz

Learning mmcv is rewarding since, all mm-series share the same architectural design. You will master [pose](https://github.com/open-mmlab/mmpose)/[segmentation](https://github.com/open-mmlab/mmsegmentation)/[detection](https://github.com/open-mmlab/mmdetection)/[action](https://github.com/open-mmlab/mmaction2)/[super-resulution](https://github.com/open-mmlab/mmediting)/... for free once you know it. The heart of mmcv is the registry system...

@Whatsetsthisend Thanks for your contribution! Sure please make the pull request so that it could help more people

Hi @usamaamjad7, please open a new issue for new questions :)

~~Please checkout https://mmocr.readthedocs.io/en/latest/textdet_models.html#psenet~~ I see, the link was wrong. Thanks for the report!

Thanks for the recommendation. It is not planned for the next two month. We will add it to backlog. Follow our iteration plan for updates!

hi, which script was run? currently the inference code is not optimized yet. see https://github.com/open-mmlab/mmpose/issues/40. you may vote here https://github.com/open-mmlab/mmpose/issues/9 to help us prioritize

thanks! it would be great if people can help with profiling and identifying the bottleneck. here is some guide we wrote earlier (can safely omit the Chinese characters and guess...

If you have interest, please try to profile it and post the result, something like https://github.com/open-mmlab/mmpose/issues/344#issuecomment-752895676

Step1. use cProfile to run the script for a period of time, say, 30 seconds.  Step2. visualize the result by snakeviz  Refer to the instruction in https://github.com/open-mmlab/mmpose/issues/73#issuecomment-676822565 for...

Please expand shared_transformation section, by clicking on it