taining_data

README.md

@@ -1,5 +1,59 @@
 # monocon_rp (2022.08.10)
-此项目用于复现monocon
+此项目用于复现monocon 
+源码地址：https://github.com/chenzihao008/monocon-pytorch.git
 ## environment
 - [显卡] 3080*1 10G
 - [CUDA] 10.1
+## 复现数据集
+- [kitti] https://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d
+- [训练:验证数据比例] 3712:3769
+## setting
+- [batch] 8
+- [epoch] 100
+## traget创建方式
+
+## 训练记录
+- [time/epoch] 5-7mins
+- [epoch:115] 
+----------- Eval Results ------------
+Pedestrian AP40@0.50, 0.50, 0.50:
+bbox AP40:49.6264, 39.1815, 32.5803
+bev  AP40:2.4284, 2.0529, 1.8834
+3d   AP40:2.1300, 1.7796, 1.3170
+aos  AP40:39.36, 30.62, 25.27
+Pedestrian AP40@0.50, 0.25, 0.25:
+bbox AP40:49.6264, 39.1815, 32.5803
+bev  AP40:13.6819, 10.8073, 9.4292
+3d   AP40:13.1637, 10.4792, 9.0917
+aos  AP40:39.36, 30.62, 25.27
+Cyclist AP40@0.50, 0.50, 0.50:
+bbox AP40:61.2945, 33.7005, 31.3321
+bev  AP40:4.5178, 2.2949, 2.1737
+3d   AP40:3.7567, 1.9922, 1.5229
+aos  AP40:55.24, 30.34, 28.10
+Cyclist AP40@0.50, 0.25, 0.25:
+bbox AP40:61.2945, 33.7005, 31.3321
+bev  AP40:19.9975, 10.6099, 9.3342
+3d   AP40:19.6833, 10.3631, 9.1433
+aos  AP40:55.24, 30.34, 28.10
+Car AP40@0.70, 0.70, 0.70:
+bbox AP40:96.0738, 78.1678, 70.8113
+bev  AP40:17.5216, 10.9126, 9.0341
+3d   AP40:9.7757, 6.3920, 5.1801
+aos  AP40:94.61, 76.57, 68.84
+Car AP40@0.70, 0.50, 0.50:
+bbox AP40:96.0738, 78.1678, 70.8113
+bev  AP40:51.2260, 32.1783, 27.4159
+3d   AP40:44.6220, 28.2990, 22.9361
+aos  AP40:94.61, 76.57, 68.84
+
+Overall AP40@easy, moderate, hard:
+bbox AP40:68.9982, 50.3499, 44.9079
+bev  AP40:8.1559, 5.0868, 4.3637
+3d   AP40:5.2208, 3.3879, 2.6733
+aos  AP40:63.07, 45.85, 40.74
+- [training_loss]
+ ![Image text](training_log/Snipaste_2023-11-17_10-28-16.png)
+
+## 优化策略及数据对比
+## 知识补充