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15 changes: 14 additions & 1 deletion readme.md
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,18 @@ If you utilize this framework, please cite our ICCV 2019 paper.

- **Data**

Download the full [KITTI](http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) detection dataset. Then place a softlink (or the actual data) in *M3D-RPN/data/kitti*.
Download the full [KITTI](http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) detection dataset.
All data should be inside training and testing folder, for ex.

```
training/calib/,
training/image_2/,
testing/image_2/,
testing/calib/
and etc.
```

Then place a softlink (or the actual data) in *M3D-RPN/data/kitti*.

```
cd M3D-RPN
Expand Down Expand Up @@ -86,6 +97,8 @@ python scripts/train_rpn_3d.py --config=kitti_3d_multi_main --restore=10000

We provide models for the main experiments on val1 / val2 / test data splits available to download here [M3D-RPN-Release.zip](https://www.cse.msu.edu/computervision/M3D-RPN-Release.zip).

Unzip the archive and put it inside *data* folder

Testing requires paths to the configuration file and model weights, exposed variables near the top *scripts/test_rpn_3d.py*. To test a configuration and model, simply update the variables and run the test file as below.

```
Expand Down
6 changes: 3 additions & 3 deletions scripts/test_rpn_3d.py
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Expand Up @@ -18,8 +18,8 @@
# -----------------------------------------
from lib.imdb_util import *

conf_path = '/home/garrick/Desktop/M3D-RPN-Release/m3d_rpn_depth_aware_test_config.pkl'
weights_path = '/home/garrick/Desktop/M3D-RPN-Release/m3d_rpn_depth_aware_test'
conf_path = 'data/M3D-RPN-Release/m3d_rpn_depth_aware_test_config.pkl'
weights_path = 'data/M3D-RPN-Release/m3d_rpn_depth_aware_test'

# load config
conf = edict(pickle_read(conf_path))
Expand Down Expand Up @@ -57,4 +57,4 @@
# test kitti
# -----------------------------------------

test_kitti_3d(conf.dataset_test, net, conf, results_path, data_path, use_log=False)
test_kitti_3d(conf.dataset_test, net, conf, results_path, data_path, use_log=False)