From a3e2b2ea765b4b0f8880a30dd244cbd1f1fc5ad4 Mon Sep 17 00:00:00 2001 From: George Ni Date: Thu, 29 Jul 2021 19:13:35 +0800 Subject: [PATCH] [cherry-pick][MOT]Add kitti metric (#3821) * add kitti metric * clean kitti metric code * fix kitticars doc * fix feature model cfgs * add kitti metric --- configs/mot/README.md | 23 + configs/mot/README_cn.md | 23 + configs/mot/headtracking21/README.md | 1 + .../{fairmot => }/headtracking21/README_cn.md | 48 +- ...rmot_dla34_30e_1088x608_headtracking21.yml | 7 +- configs/mot/kitticars/README.md | 1 + configs/mot/kitticars/README_cn.md | 76 ++ .../fairmot_dla34_30e_1088x608_kitticars.yml | 27 + deploy/python/mot_jde_infer.py | 1 + deploy/python/mot_keypoint_unite_infer.py | 1 + deploy/python/mot_sde_infer.py | 1 + docs/images/kitticars_fairmot.gif | Bin 0 -> 2603630 bytes ppdet/engine/tracker.py | 10 +- ppdet/metrics/mot_metrics.py | 931 +++++++++++++++++- ppdet/metrics/munkres.py | 428 ++++++++ tools/eval_mot.py | 7 +- tools/infer_mot.py | 7 +- 17 files changed, 1537 insertions(+), 55 deletions(-) create mode 120000 configs/mot/headtracking21/README.md rename configs/mot/{fairmot => }/headtracking21/README_cn.md (62%) rename configs/mot/{fairmot => }/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml (80%) create mode 120000 configs/mot/kitticars/README.md create mode 100644 configs/mot/kitticars/README_cn.md create mode 100755 configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml create mode 100644 docs/images/kitticars_fairmot.gif create mode 100644 ppdet/metrics/munkres.py diff --git a/configs/mot/README.md b/configs/mot/README.md index 06c077dc1..f5debaab4 100644 --- a/configs/mot/README.md +++ b/configs/mot/README.md @@ -6,6 +6,7 @@ English | [简体中文](README_cn.md) - [Introduction](#Introduction) - [Installation](#Installation) - [Model Zoo](#Model_Zoo) +- [Feature Tracking Model](#Feature_Tracking_Model) - [Dataset Preparation](#Dataset_Preparation) - [Getting Start](#Getting_Start) - [Citations](#Citations) @@ -131,6 +132,28 @@ If you use a stronger detection model, you can get better results. Each txt is t FairMOT used 8 GPUs for training and mini-batch size as 6 on each GPU, and trained for 30 epoches. +## Feature Tracking Model + +### 【Head Tracking](./headtracking21/README.md) + +### FairMOT Results on HT-21 Training Set +| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config | +| :--------------| :------- | :----: | :----: | :---: | :----: | :---: | :------: | :----: |:----: | +| DLA-34 | 1088x608 | 67.2 | 70.4 | 9403 | 124840 | 255007 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | + +### FairMOT Results on HT-21 Test Set +| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config | +| :--------------| :------- | :----: | :----: | :----: | :----: | :----: |:-------: | :----: | :----: | +| DLA-34 | 1088x608 | 58.2 | 61.3 | 13166 | 141872 | 197074 | - | [model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | + +### [Vehicle Tracking](./kitticars/README.md) +### FairMOT Results on KITTI tracking (2D bounding-boxes) Training Set (Car) + +| backbone | input shape | MOTA | FPS | download | config | +| :--------------| :------- | :-----: | :-----: | :------: | :----: | +| DLA-34 | 1088x608 | 67.9 | - |[model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_kitticars.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml) | + + ## Dataset Preparation ### MOT Dataset diff --git a/configs/mot/README_cn.md b/configs/mot/README_cn.md index 167f589e8..ff430d899 100644 --- a/configs/mot/README_cn.md +++ b/configs/mot/README_cn.md @@ -7,6 +7,7 @@ - [安装依赖](#安装依赖) - [模型库](#模型库) - [数据集准备](#数据集准备) +- [特色垂类跟踪模型](#特色垂类跟踪模型) - [快速开始](#快速开始) - [引用](#引用) @@ -131,6 +132,28 @@ wget https://dataset.bj.bcebos.com/mot/det_results_dir.zip FairMOT使用8个GPU进行训练,每个GPU上batch size为6,训练30个epoch。 +## 特色垂类跟踪模型 + +### 【人头跟踪(Head Tracking)](./headtracking21/README.md) + +### FairMOT在HT-21 Training Set上结果 +| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 | +| :--------------| :------- | :----: | :----: | :---: | :----: | :---: | :------: | :----: |:----: | +| DLA-34 | 1088x608 | 67.2 | 70.4 | 9403 | 124840 | 255007 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | + +### FairMOT在HT-21 Test Set上结果 +| 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 | +| :--------------| :------- | :----: | :----: | :----: | :----: | :----: |:-------: | :----: | :----: | +| DLA-34 | 1088x608 | 58.2 | 61.3 | 13166 | 141872 | 197074 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | + +### [车辆跟踪 (Vehicle Tracking)](./kitticars/README.md) +### FairMOT在KITTI tracking (2D bounding-boxes) Training Set上Car类别的结果 + +| 骨干网络 | 输入尺寸 | MOTA | FPS | 下载链接 | 配置文件 | +| :--------------| :------- | :-----: | :-----: | :------: | :----: | +| DLA-34 | 1088x608 | 67.9 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_kitticars.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml) | + + ## 数据集准备 ### MOT数据集 diff --git a/configs/mot/headtracking21/README.md b/configs/mot/headtracking21/README.md new file mode 120000 index 000000000..4015683cf --- /dev/null +++ b/configs/mot/headtracking21/README.md @@ -0,0 +1 @@ +README_cn.md \ No newline at end of file diff --git a/configs/mot/fairmot/headtracking21/README_cn.md b/configs/mot/headtracking21/README_cn.md similarity index 62% rename from configs/mot/fairmot/headtracking21/README_cn.md rename to configs/mot/headtracking21/README_cn.md index 4a82832e1..281c5ab57 100644 --- a/configs/mot/fairmot/headtracking21/README_cn.md +++ b/configs/mot/headtracking21/README_cn.md @@ -1,35 +1,24 @@ -简体中文 | [English](README.md) +[English](README.md) | 简体中文 +# 特色垂类跟踪模型 -# FairMOT (FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking) - -## 内容 -- [简介](#简介) -- [模型库](#模型库) -- [快速开始](#快速开始) -- [引用](#引用) - -## 简介 - -[FairMOT](https://arxiv.org/abs/2004.01888)以Anchor Free的CenterNet检测器为基础,克服了Anchor-Based的检测框架中anchor和特征不对齐问题,深浅层特征融合使得检测和ReID任务各自获得所需要的特征,并且使用低维度ReID特征,提出了一种由两个同质分支组成的简单baseline来预测像素级目标得分和ReID特征,实现了两个任务之间的公平性,并获得了更高水平的实时多目标跟踪精度。 +## 人头跟踪(Head Tracking) +现有行人跟踪器对高人群密度场景表现不佳,人头跟踪更适用于密集场景的跟踪。 +[HT-21](https://motchallenge.net/data/Head_Tracking_21)是一个高人群密度拥挤场景的人头跟踪数据集,场景包括不同的光线和环境条件下的拥挤的室内和室外场景,所有序列的帧速率都是25fps。
- +
## 模型库 - ### FairMOT在HT-21 Training Set上结果 - | 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 | | :--------------| :------- | :----: | :----: | :---: | :----: | :---: | :------: | :----: |:----: | -| DLA-34 | 1088x608 | 67.2 | 70.4 | 9403 | 124840 | 255007 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | - +| DLA-34 | 1088x608 | 67.2 | 70.4 | 9403 | 124840 | 255007 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | ### FairMOT在HT-21 Test Set上结果 - | 骨干网络 | 输入尺寸 | MOTA | IDF1 | IDS | FP | FN | FPS | 下载链接 | 配置文件 | | :--------------| :------- | :----: | :----: | :----: | :----: | :----: |:-------: | :----: | :----: | -| DLA-34 | 1088x608 | 58.2 | 61.3 | 13166 | 141872 | 197074 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | +| DLA-34 | 1088x608 | 58.2 | 61.3 | 13166 | 141872 | 197074 | - | [下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml) | **注意:** FairMOT使用8个GPU进行训练,每个GPU上batch size为6,训练30个epoch。 @@ -37,53 +26,42 @@ ## 快速开始 ### 1. 训练 - 使用8GPU通过如下命令一键式启动训练 - ```bash -python -m paddle.distributed.launch --log_dir=./fairmot_dla34_30e_1088x608_headtracking21/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml +python -m paddle.distributed.launch --log_dir=./fairmot_dla34_30e_1088x608_headtracking21/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml ``` - ### 2. 评估 - 使用单张GPU通过如下命令一键式启动评估 - ```bash # 使用PaddleDetection发布的权重 -CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams +CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams # 使用训练保存的checkpoint -CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=output/fairmot_dla34_30e_1088x608_headtracking21/model_final.pdparams +CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=output/fairmot_dla34_30e_1088x608_headtracking21/model_final.pdparams ``` - ### 3. 预测 - 使用单个GPU通过如下命令预测一个视频,并保存为视频 - ```bash # 预测一个视频 -CUDA_VISIBLE_DEVICES=0 python tools/infer_mot.py -c configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams --video_file={your video name}.mp4 --save_videos +CUDA_VISIBLE_DEVICES=0 python tools/infer_mot.py -c configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams --video_file={your video name}.mp4 --save_videos ``` **注意:** 请先确保已经安装了[ffmpeg](https://ffmpeg.org/ffmpeg.html), Linux(Ubuntu)平台可以直接用以下命令安装:`apt-get update && apt-get install -y ffmpeg`。 ### 4. 导出预测模型 - ```bash -CUDA_VISIBLE_DEVICES=0 python tools/export_model.py -c configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams +CUDA_VISIBLE_DEVICES=0 python tools/export_model.py -c configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_headtracking21.pdparams ``` ### 5. 用导出的模型基于Python去预测 - ```bash python deploy/python/mot_jde_infer.py --model_dir=output_inference/fairmot_dla34_30e_1088x608_headtracking21 --video_file={your video name}.mp4 --device=GPU --save_mot_txts ``` **注意:** 跟踪模型是对视频进行预测,不支持单张图的预测,默认保存跟踪结果可视化后的视频,可添加`--save_mot_txts`表示保存跟踪结果的txt文件,或`--save_images`表示保存跟踪结果可视化图片。 - ## 引用 ``` @article{zhang2020fair, diff --git a/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml b/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml similarity index 80% rename from configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml rename to configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml index ac3aa657d..8bfbc7ca8 100755 --- a/configs/mot/fairmot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml +++ b/configs/mot/headtracking21/fairmot_dla34_30e_1088x608_headtracking21.yml @@ -1,7 +1,8 @@ _BASE_: [ - '../fairmot_dla34_30e_1088x608.yml' + '../fairmot/fairmot_dla34_30e_1088x608.yml' ] +weights: output/fairmot_dla34_30e_1088x608_headtracking21/model_final # for MOT training TrainDataset: @@ -11,7 +12,7 @@ TrainDataset: data_fields: ['image', 'gt_bbox', 'gt_class', 'gt_ide'] # for MOT evaluation -# If you want to change the MOT evaluation dataset, please modify 'task' and 'data_root' +# If you want to change the MOT evaluation dataset, please modify 'data_root' EvalMOTDataset: !MOTImageFolder dataset_dir: dataset/mot @@ -20,6 +21,6 @@ EvalMOTDataset: # for MOT video inference TestMOTDataset: - !MOTVideoDataset + !MOTImageFolder dataset_dir: dataset/mot keep_ori_im: True # set True if save visualization images or video diff --git a/configs/mot/kitticars/README.md b/configs/mot/kitticars/README.md new file mode 120000 index 000000000..4015683cf --- /dev/null +++ b/configs/mot/kitticars/README.md @@ -0,0 +1 @@ +README_cn.md \ No newline at end of file diff --git a/configs/mot/kitticars/README_cn.md b/configs/mot/kitticars/README_cn.md new file mode 100644 index 000000000..bd9f0bade --- /dev/null +++ b/configs/mot/kitticars/README_cn.md @@ -0,0 +1,76 @@ +[English](README.md) | 简体中文 +# 特色垂类跟踪模型 + +## 车辆跟踪 (Vehicle Tracking) + +车辆跟踪的主要应用之一是交通监控。 +[KITTI-Tracking](http://www.cvlibs.net/datasets/kitti/eval_tracking.php)是一个包含市区、乡村和高速公路等场景采集的数据集,每张图像中最多达15辆车和30个行人,还有各种程度的遮挡与截断。其中用于目标跟踪的数据集一共有50个视频序列,21个为训练集,29个为测试集,目标是估计类别“Car”和”Pedestrian“的目标轨迹,此处只使用类别“Car”。 +
+ +
+ +## 模型库 + +### FairMOT在KITTI tracking (2D bounding-boxes) Training Set上Car类别的结果 + +| 骨干网络 | 输入尺寸 | MOTA | FPS | 下载链接 | 配置文件 | +| :--------------| :------- | :-----: | :-----: | :------: | :----: | +| DLA-34 | 1088x608 | 67.9 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_kitticars.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.2/configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml) | + +**注意:** + FairMOT使用8个GPU进行训练,每个GPU上batch size为6,训练30个epoch。 + +## 快速开始 + +### 1. 训练 +使用8GPU通过如下命令一键式启动训练 +```bash +python -m paddle.distributed.launch --log_dir=./fairmot_dla34_30e_1088x608_kitticars/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml +``` + +### 2. 评估 +使用单张GPU通过如下命令一键式启动评估 +```bash +# 使用PaddleDetection发布的权重 +CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_kitticars.pdparams + +# 使用训练保存的checkpoint +CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml -o weights=output/fairmot_dla34_30e_1088x608_kitticars/model_final.pdparams +``` + +### 3. 预测 +使用单个GPU通过如下命令预测一个视频,并保存为视频 +```bash +# 预测一个视频 +CUDA_VISIBLE_DEVICES=0 python tools/infer_mot.py -c configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_kitticars.pdparams --video_file={your video name}.mp4 --save_videos +``` +**注意:** + 请先确保已经安装了[ffmpeg](https://ffmpeg.org/ffmpeg.html), Linux(Ubuntu)平台可以直接用以下命令安装:`apt-get update && apt-get install -y ffmpeg`。 + +### 4. 导出预测模型 +```bash +CUDA_VISIBLE_DEVICES=0 python tools/export_model.py -c configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml -o weights=https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_kitticars.pdparams +``` + +### 5. 用导出的模型基于Python去预测 +```bash +python deploy/python/mot_jde_infer.py --model_dir=output_inference/fairmot_dla34_30e_1088x608_kitticars --video_file={your video name}.mp4 --device=GPU --save_mot_txts +``` +**注意:** + 跟踪模型是对视频进行预测,不支持单张图的预测,默认保存跟踪结果可视化后的视频,可添加`--save_mot_txts`表示保存跟踪结果的txt文件,或`--save_images`表示保存跟踪结果可视化图片。 + +## 引用 +``` +@article{zhang2020fair, + title={FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking}, + author={Zhang, Yifu and Wang, Chunyu and Wang, Xinggang and Zeng, Wenjun and Liu, Wenyu}, + journal={arXiv preprint arXiv:2004.01888}, + year={2020} +} +@INPROCEEDINGS{Geiger2012CVPR, + author = {Andreas Geiger and Philip Lenz and Raquel Urtasun}, + title = {Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite}, + booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)}, + year = {2012} +} +``` diff --git a/configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml b/configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml new file mode 100755 index 000000000..a103cba6c --- /dev/null +++ b/configs/mot/kitticars/fairmot_dla34_30e_1088x608_kitticars.yml @@ -0,0 +1,27 @@ +_BASE_: [ + '../fairmot/fairmot_dla34_30e_1088x608.yml' +] + +metric: KITTI +weights: output/fairmot_dla34_30e_1088x608_kitticars/model_final + +# for MOT training +TrainDataset: + !MOTDataSet + dataset_dir: dataset/mot + image_lists: ['kitticars.train'] + data_fields: ['image', 'gt_bbox', 'gt_class', 'gt_ide'] + +# for MOT evaluation +# If you want to change the MOT evaluation dataset, please modify 'data_root' +EvalMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + data_root: kitticars/images/test + keep_ori_im: False # set True if save visualization images or video, or used in DeepSORT + +# for MOT video inference +TestMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + keep_ori_im: True # set True if save visualization images or video diff --git a/deploy/python/mot_jde_infer.py b/deploy/python/mot_jde_infer.py index 021e5aea7..103cf4585 100644 --- a/deploy/python/mot_jde_infer.py +++ b/deploy/python/mot_jde_infer.py @@ -179,6 +179,7 @@ def write_mot_results(filename, results, data_type='mot'): def predict_image(detector, image_list): results = [] + image_list.sort() for i, img_file in enumerate(image_list): frame = cv2.imread(img_file) if FLAGS.run_benchmark: diff --git a/deploy/python/mot_keypoint_unite_infer.py b/deploy/python/mot_keypoint_unite_infer.py index 46ecefe78..2db100c2d 100644 --- a/deploy/python/mot_keypoint_unite_infer.py +++ b/deploy/python/mot_keypoint_unite_infer.py @@ -56,6 +56,7 @@ def mot_keypoint_unite_predict_image(mot_model, keypoint_model, image_list, keypoint_batch_size=1): + image_list.sort() for i, 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