diff --git a/README.md b/README.md index f57423d..73aa67b 100644 --- a/README.md +++ b/README.md @@ -12,6 +12,8 @@ OpenGait is a flexible and extensible gait recognition project provided by the [ - **AMP Support**: The [`Auto Mixed Precision (AMP)`](https://pytorch.org/tutorials/recipes/recipes/amp_recipe.html?highlight=amp) option is available. - **Nice log**: We use [`tensorboard`](https://pytorch.org/docs/stable/tensorboard.html) and `logging` to log everything, which looks pretty. +## What's New +- [Mar 2022] [HID](http://hid2022.iapr-tc4.org/) support is ready in [misc/HID](./misc/HID). ## Model Zoo diff --git a/misc/HID/README.md b/misc/HID/README.md index 2f22ae2..01a744e 100644 --- a/misc/HID/README.md +++ b/misc/HID/README.md @@ -1,5 +1,6 @@ # HID Tutorial -This is the official suppor for competition of Human Identification at a Distance (HID). We report our result is 68.7% using the baseline model. In order for participants to better start the first step, we provide a tutorial on how to use OpenGait for HID. +![](http://hid2022.iapr-tc4.org/wp-content/uploads/sites/7/2022/03/%E5%9B%BE%E7%89%871-2.png) +This is the official support for competition of [Human Identification at a Distance (HID)](http://hid2022.iapr-tc4.org/). We report our result is 68.7% using the baseline model. In order for participants to better start the first step, we provide a tutorial on how to use OpenGait for HID. ## Preprocess the dataset Download the raw dataset from the [official link](http://hid2022.iapr-tc4.org/). You will get three compressed files, i.e. `train.tar`, `HID2022_test_gallery.zip` and `HID2022_test_probe.zip`. @@ -13,7 +14,7 @@ Modify the `dataset_root` in `./misc/HID/baseline_hid.yaml`, and then run this c ```shell CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 lib/main.py --cfgs ./misc/HID/baseline_hid.yaml --phase train ``` -You can also download the [trained model](https://github.com/ShiqiYu/OpenGait/releases/download/v1.1/pretrained_hid_model.pt) and place it in `output` after unzipping. +You can also download the [trained model](https://github.com/ShiqiYu/OpenGait/releases/download/v1.1/pretrained_hid_model.zip) and place it in `output` after unzipping. ## Get the submission file. ```shell