meituan / YOLOv6

YOLOv6: a single-stage object detection framework dedicated to industrial applications.
GNU General Public License v3.0
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【YOLOv6 VS PP-YOLOE s(400 epoch) Update】官方性能实测更新 / Update of the Official Performance Comparison #235

Closed YixinKristy closed 1 year ago

YixinKristy commented 2 years ago

Update of the Test Result after Training 400 Epoch of PP-YOLOE s

Here is the latest comparison result:

Model epoch AP 0.5:0.95 AP 0.5 AP 0.75 AP small AP medium AP large AR small AR medium AR large
PP-YOLOE s 300 43.0 59.6 47.2 26.0 47.4 58.7 45.1 70.6 81.4
PP-YOLOE s  400 43.4 60.0 47.5 25.7 47.8 59.2 43.9 70.8 81.9
YOLOv6 s 400 43.1 62.0 46.2 23.9 47.4 58.8 40.2 65.5 76.4

Feel free to raise any question or suggestion about the result~ PP-YOLOE always respect the original work of YOLO series and we'll keep working on providing more high-quality models.

For more reference: https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/ppyoloe

The original issue with complete test result: https://github.com/meituan/YOLOv6/issues/140

性能对比测试数据更新(PP-YOLOE s训练400 epoch后)

2022.7.5日更新:

由于收到大家的反馈,我们训练针对PP-YOLOE s版本训练了400 epoch,以下是对比效果:

模型 epoch AP 0.5:0.95 AP 0.5 AP 0.75 AP small AP medium AP large AR small AR medium AR large
PP-YOLOE s 300 43.0 59.6 47.2 26.0 47.4 58.7 45.1 70.6 81.4
PP-YOLOE s 400 43.4 60.0 47.5 25.7 47.8 59.2 43.9 70.8 81.9
YOLOv6 s 400 43.1 62.0 46.2 23.9 47.4 58.8 40.2 65.5 76.4

大家有任何问题欢迎在评论区中讨论提出~

PP-YOLOE始终保持着向YOLO系列的致敬,希望大家能多多尝试,提出宝贵的建议! 如需获取完整的对比测试,请参考原始issue:https://github.com/meituan/YOLOv6/issues/140

hutao568 commented 2 years ago

美团:这是来砸场子的吗Σ(⊙▽⊙"a

qmcreeper commented 1 year ago

美团:这是来砸场子的吗Σ(⊙▽⊙"a

再来个yolov7的对比就更有意思了 : P