pytorch 使用centernet进行 人脸检测Face Detection (bbox + landmark)、 船只检测SeaShips Detection
使用CenterNet来训练其他数据。
测试：使用原图分辨率，未使用Multi Scale，在验证集上进行测试。
| Backbone | AP | AP50 | AP75 | APS | APM | APL |
|---|---|---|---|---|---|---|
| DLA-34 | 43.7 | 73.7 | 47.7 | 31.9 | 58.8 | 64.0 |
| MobileNet-V2 | 34.3 | 62.0 | 35.0 | 27.2 | 52.4 | 42.7 |
测试：使用原图分辨率，未使用Multi Scale，在验证集和测试集上进行测试。
| Backbone | 数据集 | AP | AP50 | AP75 | APS | APM | APL |
|---|---|---|---|---|---|---|---|
| DLA-34 | Val | 21.3 | 37.3 | 21.5 | 10.8 | 39.3 | 22.1 |
| DLA-34 | Test | 21.6 | 36.4 | 23.5 | 2.7 | 32.4 | 22.8 |
Thanks for your work!!!
I use this repo to detec my own plate dataset,when I finally get my train model ,this result is just ok ,but the confidence score is usually between from 0.4-0.8,for dectec task this score isn't too low?when I use retinanet for detection task ,the score is usually over 0.95,so can you gave me some advices on how to make the confidence score higher?
自行训练的数据发现人脸倾斜时，关键点预测不准，在训练上有什么优化策略么？
点击seaship数据集下载链接，无法访问，是否可以提供这个数据集？
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