Commit ccc17cd1 authored by ZwwWayne's avatar ZwwWayne
Browse files

refine benchmark and model pages

parent a514165c
......@@ -21,13 +21,14 @@ with some other popular open source 3D detection codebases.
We compare our implementation of VoteNet with [votenet](https://github.com/facebookresearch/votenet/) and report the performance on SUNRGB-D v2 dataset under the AP@0.5 metric.
```eval_rst
+----------------+---------------------+--------------------+--------+
| Implementation | Training (sample/s) | Testing (sample/s) | AP@0.5 |
+================+=====================+====================+========+
| MMDetection3D | 358 | 17 | 35.8 |
+----------------+---------------------+--------------------+--------+
| VoteNet | 77 | 3 | 31.5 |
+----------------+---------------------+--------------------+--------+
+----------------+---------------------+--------------------+--------+
| Implementation | Training (sample/s) | Testing (sample/s) | AP@0.5 |
+================+=====================+====================+========+
| MMDetection3D | 358 | 17 | 35.8 |
+----------------+---------------------+--------------------+--------+
| votenet_ | 77 | 3 | 31.5 |
+----------------+---------------------+--------------------+--------+
```
### PointPillars
......@@ -38,23 +39,23 @@ condition following the KITTI benchmark and compare average AP over all classes
performance on 3 classes.
```eval_rst
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 141 | 44.3 |
+----------------+---------------------+--------------------+
| Det3D | 140 | 20 |
+----------------+---------------------+--------------------+
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 141 | 44.3 |
+----------------+---------------------+--------------------+
| Det3D | 140 | 20 |
+----------------+---------------------+--------------------+
```
```eval_rst
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 120 | |
+----------------+---------------------+--------------------+
| PCDet | 43 | 64 |
+----------------+---------------------+--------------------+
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 120 | |
+----------------+---------------------+--------------------+
| PCDet | 43 | 64 |
+----------------+---------------------+--------------------+
```
### SECOND
......@@ -64,30 +65,30 @@ So we only compare with [PCDet](https://github.com/sshaoshuai/PCDet), which is a
condition following the KITTI benchmark and compare average AP over all classes on moderate condition for
performance on 3 classes.
```eval_rst
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 54 | |
+----------------+---------------------+--------------------+
| PCDet | 44 | 30 |
+----------------+---------------------+--------------------+
```
```eval_rst
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 54 | |
+----------------+---------------------+--------------------+
| PCDet | 44 | 30 |
+----------------+---------------------+--------------------+
```
### Part-A2
We benchmark Part-A2 with that in [PCDet](https://github.com/sshaoshuai/PCDet). We report the AP on moderate condition following the KITTI benchmark
and compare average AP over all classes on moderate condition for performance on 3 classes.
```eval_rst
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 17 | |
+----------------+---------------------+--------------------+
| PCDet | 15 | 12 |
+----------------+---------------------+--------------------+
```
```eval_rst
+----------------+---------------------+--------------------+
| Implementation | Training (sample/s) | Testing (sample/s) |
+================+=====================+====================+
| MMDetection3D | 17 | |
+----------------+---------------------+--------------------+
| PCDet | 15 | 12 |
+----------------+---------------------+--------------------+
```
## Details of Comparison
......@@ -128,28 +129,36 @@ python train.py --dataset sunrgbd --batch_size 16
./tools/dist_train.sh configs/benchmark/hv_pointpillars_secfpn_3x8_100e_det3d_kitti-3d-car.py 8 --no-validate
```
* __Det3D__: At commit 255c593, use kitti_point_pillars_mghead_syncbn.py and run
```
./tools/scripts/train.sh --launcher=slurm --gpus=8
```
Note that the config in train.sh is modified to train point pillars.
```
diff --git a/tools/scripts/train.sh b/tools/scripts/train.sh
index 3a93f95..461e0ea 100755
--- a/tools/scripts/train.sh
+++ b/tools/scripts/train.sh
@@ -16,9 +16,9 @@ then
fi
# Voxelnet
-python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/second/configs/kitti_car_vfev3_spmiddlefhd_rpn1_mghead_syncbn.py --work_dir=$SECOND_WORK_DIR
+# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/second/configs/kitti_car_vfev3_spmiddlefhd_rpn1_mghead_syncbn.py --work_dir=$SECOND_WORK_DIR
# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/cbgs/configs/nusc_all_vfev3_spmiddleresnetfhd_rpn2_mghead_syncbn.py --work_dir=$NUSC_CBGS_WORK_DIR
# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/second/configs/lyft_all_vfev3_spmiddleresnetfhd_rpn2_mghead_syncbn.py --work_dir=$LYFT_CBGS_WORK_DIR
```
./tools/scripts/train.sh --launcher=slurm --gpus=8
```
Note that the config in train.sh is modified to train point pillars.
<details>
<summary>
(diff to make it use the same hyperparameters - click to expand)
</summary>
```diff
diff --git a/tools/scripts/train.sh b/tools/scripts/train.sh
index 3a93f95..461e0ea 100755
--- a/tools/scripts/train.sh
+++ b/tools/scripts/train.sh
@@ -16,9 +16,9 @@ then
fi
# Voxelnet
-python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/second/configs/ kitti_car_vfev3_spmiddlefhd_rpn1_mghead_syncbn.py --work_dir=$SECOND_WORK_DIR
+# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/second/configs/ kitti_car_vfev3_spmiddlefhd_rpn1_mghead_syncbn.py --work_dir=$SECOND_WORK_DIR
# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/cbgs/configs/ nusc_all_vfev3_spmiddleresnetfhd_rpn2_mghead_syncbn.py --work_dir=$NUSC_CBGS_WORK_DIR
# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py examples/second/configs/ lyft_all_vfev3_spmiddleresnetfhd_rpn2_mghead_syncbn.py --work_dir=$LYFT_CBGS_WORK_DIR
# PointPillars
-# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py ./examples/point_pillars/configs/ original_pp_mghead_syncbn_kitti.py --work_dir=$PP_WORK_DIR
+python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py ./examples/point_pillars/configs/ kitti_point_pillars_mghead_syncbn.py
```
# PointPillars
-# python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py ./examples/point_pillars/configs/original_pp_mghead_syncbn_kitti.py --work_dir=$PP_WORK_DIR
+python -m torch.distributed.launch --nproc_per_node=8 ./tools/train.py ./examples/point_pillars/configs/kitti_point_pillars_mghead_syncbn.py
```
</details>
### SECOND
......
# Benchmark and Model Zoo
# Model Zoo
## Mirror sites
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment