From 513a78b44272e75fd654b29b16000cd718705c4f Mon Sep 17 00:00:00 2001 From: zyayoung <1328410180@qq.com> Date: Fri, 11 Feb 2022 21:53:40 +0800 Subject: [PATCH] results on dance track and minor fix --- .gitignore | 8 ++++++++ README.md | 15 +++++++++++++-- datasets/dance.py | 2 +- models/motr.py | 1 + submit_dance.py | 4 ---- 5 files changed, 23 insertions(+), 7 deletions(-) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..559c6ce --- /dev/null +++ b/.gitignore @@ -0,0 +1,8 @@ +__pycache__/ +*.pth +*.train +exps/ +build/ +*.egg +*.egg-info +*.mp4 diff --git a/README.md b/README.md index 00d6538..431b148 100644 --- a/README.md +++ b/README.md @@ -23,6 +23,8 @@ This repository is an official implementation of the paper [MOTR: End-to-End Mul ## Updates - (2021/09/23) Report BDD100K results and release corresponding codes [motr_bdd100k](https://github.com/megvii-model/MOTR/tree/motr_bdd100k). - (2022/02/09) Higher performance achieved by not clipping the bounding boxes inside the image. +- (2022/02/11) Add checkpoint support for training on RTX 2080ti. +- (2022/02/11) Report [DanceTrack](https://github.com/DanceTrack/DanceTrack) results and [scripts](configs/r50_motr_train_dance.sh). ## Main Results @@ -32,6 +34,12 @@ This repository is an official implementation of the paper [MOTR: End-to-End Mul | :--------: | :---------: | :------------------: | :------: | :------: | :-----: | :------: | :------: | :------: | :-----------------------------------------------------------------------------------------: | | MOTR | MOT17 | MOT17+CrowdHuman Val | 71.1 | 68.4 | 2229 | 56.9 | 55.8 | 58.4 | [model](https://drive.google.com/file/d/1Utd6aqnuuOiMSQGvq4UGsnAfMpjtsW3E/view?usp=sharing) | +### DanceTrack + +| **Method** | **Dataset** | **Train Data** | **MOTA** | **IDF1** | **HOTA** | **AssA** | **DetA** | **URL** | +| :--------: | :---------: | :------------: | :------: | :------: | :------: | :------: | :------: | :-----------------------------------------------------------------------------------------: | +| MOTR | DanceTrack | DanceTrack | 79.7 | 51.5 | 54.2 | 40.2 | 73.5 | [model](https://drive.google.com/file/d/1zs5o1oK8diafVfewRl3heSVQ7-XAty3J/view?usp=sharing) | + ### BDD100K | **Method** | **Dataset** | **Train Data** | **MOTA** | **IDF1** | **IDS** | **URL** | @@ -40,8 +48,8 @@ This repository is an official implementation of the paper [MOTR: End-to-End Mul *Note:* -1. All models of MOTR are trained on 8 NVIDIA Tesla V100 GPUs. -2. The training time is about 2.5 days for 200 epochs; +1. MOTR on MOT17 and DanceTrack is trained on 8 NVIDIA RTX 2080ti GPUs. +2. The training time for MOT17 is about 2.5 days on V100 or 4 days on RTX 2080ti; 3. The inference speed is about 7.5 FPS for resolution 1536x800; 4. All models of MOTR are trained with ResNet50 with pre-trained weights on COCO dataset. @@ -102,6 +110,9 @@ The codebase is built on top of [Deformable DETR](https://github.com/fundamental ├── MOT17 │   ├── images │   ├── labels_with_ids +├── DanceTrack +│   ├── train +│   ├── test ├── bdd100k │   ├── images │ ├── track diff --git a/datasets/dance.py b/datasets/dance.py index 834fd1b..cf80a18 100644 --- a/datasets/dance.py +++ b/datasets/dance.py @@ -253,5 +253,5 @@ def build(image_set, args): dataset = DetMOTDetection(args, data_txt_path=data_txt_path, seqs_folder=root, dataset2transform=dataset2transform) if image_set == 'val': data_txt_path = args.data_txt_path_val - dataset = DetMOTDetection(args, data_txt_path=data_txt_path, seqs_folder=root, dataset2transform=dataset2transform, joint=False) + dataset = DetMOTDetection(args, data_txt_path=data_txt_path, seqs_folder=root, dataset2transform=dataset2transform) return dataset diff --git a/models/motr.py b/models/motr.py index a964987..c358e3f 100644 --- a/models/motr.py +++ b/models/motr.py @@ -659,6 +659,7 @@ def build(args): 'coco': 91, 'coco_panoptic': 250, 'e2e_mot': 1, + 'e2e_dance': 1, 'e2e_joint': 1, 'e2e_static_mot': 1, } diff --git a/submit_dance.py b/submit_dance.py index b4e39d8..1488f70 100644 --- a/submit_dance.py +++ b/submit_dance.py @@ -499,10 +499,6 @@ def detect(self, prob_threshold=0.7, area_threshold=100, vis=False): sub_dir = 'DanceTrack/test' seq_nums = os.listdir(os.path.join(args.mot_path, sub_dir)) - rank = int(os.environ.get('RLAUNCH_REPLICA', '0')) - ws = int(os.environ.get('RLAUNCH_REPLICA_TOTAL', '1')) - seq_nums = seq_nums[rank::ws] - for seq_num in seq_nums: det = Detector(args, model=detr, seq_num=seq_num) det.detect()