未验证 提交 b615336f 编写于 作者: F Feng Ni 提交者: GitHub

add_fairmot_airplane (#5487)

上级 0ecc2c98
......@@ -61,9 +61,9 @@ PP-tracking provides an AI studio public project tutorial. Please refer to this
| HarDNet-85 | 1088x608 | 74.7 | 70.7 | 3210 | 29790 | 109914 | - |[model](https://paddledet.bj.bcebos.com/models/mot/fairmot_enhance_hardnet85_30e_1088x608.pdparams) | [config](./fairmot_enhance_hardnet85_30e_1088x608.yml) |
**Notes:**
- FairMOT enhance used 8 GPUs for training, and the crowdhuman dataset is added to the train-set during training.
- For FairMOT enhance DLA-34 the batch size is 16 on each GPU,and trained for 60 epoches.
- For FairMOT enhance HarDNet-85 the batch size is 10 on each GPU,and trained for 30 epoches.
- FairMOT enhance used 8 GPUs for training, and the crowdhuman dataset is added to the train-set during training.
- For FairMOT enhance DLA-34 the batch size is 16 on each GPU,and trained for 60 epoches.
- For FairMOT enhance HarDNet-85 the batch size is 10 on each GPU,and trained for 30 epoches.
### FairMOT light model
### Results on MOT-16 Test Set
......@@ -100,6 +100,27 @@ PP-tracking provides an AI studio public project tutorial. Please refer to this
low_conf_thres: 0.2
```
### Fairmot transfer learning model
### Results on GMOT-40 airplane subset
| backbone | input shape | MOTA | IDF1 | IDS | FP | FN | FPS | download | config |
| :--------------| :------- | :----: | :----: | :----: | :----: | :----: | :------: | :----: |:-----: |
| DLA-34 | 1088x608 | 96.6 | 94.7 | 19 | 300 | 466 | - |[model](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_airplane.pdparams) | [config](./fairmot_dla34_30e_1088x608_airplane.yml) |
**Note:**
- The dataset of this model is a subset of airport category extracted from GMOT-40 dataset. The download link provided by the PaddleDetection team is```wget https://bj.bcebos.com/v1/paddledet/data/mot/airplane.zip```, unzip and store it in the ```dataset/mot```, and then copy the ```airplane.train``` to ```dataset/mot/image_lists```.
- FairMOT model here uses the pedestrian FairMOT trained model for pre- training weights. The train-set used is the complete set of airplane, with a total of 4 video sequences, and it also used for evaluation.
- When applied to the tracking other objects, you should modify ```min_box_area``` and ```vertical_ratio``` of the tracker in the corresponding config file, like this:
```
JDETracker:
conf_thres: 0.4
tracked_thresh: 0.4
metric_type: cosine
min_box_area: 0 # 200 for pedestrian
vertical_ratio: 0 # 1.6 for pedestrian
```
## Getting Start
### 1. Training
......
......@@ -97,6 +97,26 @@ PP-Tracking 提供了AI Studio公开项目案例,教程请参考[PP-Tracking
low_conf_thres: 0.2
```
### FairMOT迁移学习模型
### 在GMOT-40的airplane子集上的结果
| 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 | 96.6 | 94.7 | 19 | 300 | 466 | - |[下载链接](https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608_airplane.pdparams) | [配置文件](./fairmot_dla34_30e_1088x608_airplane.yml) |
**注意:**
- 此模型数据集是GMOT-40的airplane类别抽离出来的子集,PaddleDetection团队整理后的下载链接为: ```wget https://bj.bcebos.com/v1/paddledet/data/mot/airplane.zip```,下载解压存放于 ```dataset/mot```目录下,并将其中的```airplane.train```复制存放于```dataset/mot/image_lists```
- FairMOT模型此处训练是采用行人FairMOT训好的模型作为预训练权重,使用的训练集是airplane全集共4个视频序列,验证也是在全集上测的。
- 应用到其他物体的跟踪,需要更改对应的config文件里的tracker部分的```min_box_area``````vertical_ratio```,如下所示:
```
JDETracker:
conf_thres: 0.4
tracked_thresh: 0.4
metric_type: cosine
min_box_area: 0 # 200 for pedestrian
vertical_ratio: 0 # 1.6 for pedestrian
```
## 快速开始
### 1. 训练
......
......@@ -43,3 +43,5 @@ JDETracker:
conf_thres: 0.4
tracked_thresh: 0.4
metric_type: cosine
min_box_area: 200
vertical_ratio: 1.6 # for pedestrian
......@@ -39,3 +39,5 @@ JDETracker:
conf_thres: 0.4
tracked_thresh: 0.4
metric_type: cosine
min_box_area: 200
vertical_ratio: 1.6 # for pedestrian
......@@ -34,3 +34,5 @@ JDETracker:
conf_thres: 0.4
tracked_thresh: 0.4
metric_type: cosine
min_box_area: 200
vertical_ratio: 1.6 # for pedestrian
_BASE_: [
'fairmot_dla34_30e_1088x608.yml',
]
pretrain_weights: https://paddledet.bj.bcebos.com/models/mot/fairmot_dla34_30e_1088x608.pdparams
weights: output/fairmot_dla34_30e_1088x608_airplane/model_final
JDETracker:
conf_thres: 0.4
tracked_thresh: 0.4
metric_type: cosine
min_box_area: 0
vertical_ratio: 0
# for MOT training
TrainDataset:
!MOTDataSet
dataset_dir: dataset/mot
image_lists: ['airplane.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: airplane/images/train
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
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