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Any updates on HVNet on KITTI dataset
Hi
Any updates on HVNet on KITTI dataset. Do you have train/evaluation codes for kitti dataset.
Some qusetions about this project
Dear aurhor:
I'm going to get the feature like hvnet getted,but i'm confused by the variate bellow
bev_mapping_pvs = input_dict['bev_mapping_pvs']
bev_mapping_vfs = input_dict['bev_mapping_vfs']
these variate were used in your code <vfe.utils.py> class HVFeatureNetFinal's forward function
through pcdet we can transfrom data to bach_dict,which is a dict with 'frame_id','gt_boxes','points','use_lead_xyz','voxels','voxel_coords','voxel_num_points','image_shape','batch_size'
I cant understand what is 'bev_mapping_pvs' and 'bev_mapping_vfs'means
if you see my question,please replay me.thanks!
Error on AP score after test
/home/dj/anaconda3/envs/openpcdet/lib/python3.6/site-packages/numba/core/typed_passes.py:314: NumbaPerformanceWarning:
The keyword argument 'parallel=True' was specified but no transformation for parallel execution was possible.
To find out why, try turning on parallel diagnostics, see https://numba.pydata.org/numba-doc/latest/user/parallel.html#diagnostics for help.
File "../pcdet/datasets/kitti/kitti_object_eval_python/eval.py", line 120:
@numba.jit(nopython=True, parallel=True)
def d3_box_overlap_kernel(boxes, qboxes, rinc, criterion=-1):
^
state.func_ir.loc))
2021-03-10 14:49:21,966 INFO Pedestrian [email protected], 0.50, 0.50:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Pedestrian [email protected], 0.50, 0.50:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Pedestrian [email protected], 0.25, 0.25:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Pedestrian [email protected], 0.25, 0.25:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Cyclist [email protected], 0.50, 0.50:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Cyclist [email protected], 0.50, 0.50:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Cyclist [email protected], 0.25, 0.25:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Cyclist [email protected], 0.25, 0.25:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Car [email protected], 0.70, 0.70:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Car [email protected], 0.70, 0.70:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Car [email protected], 0.50, 0.50:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
Car [email protected], 0.50, 0.50:
bbox AP:0.0000, 0.0000, 0.0000
bev AP:0.0000, 0.0000, 0.0000
3d AP:0.0000, 0.0000, 0.0000
2021-03-10 14:49:21,973 INFO Result is save to /media/dj/D/code/HVNet/local/output/hvnetfinal/default/eval/epoch_80/val/default
2021-03-10 14:49:21,973 INFO Evaluation done.*
Process finished with exit code 0
Some qusetions about this project
Dear aurhor:
I'm going to get the feature like hvnet getted,but i'm confused by the variate bellow
bev_mapping_pvs = input_dict['bev_mapping_pvs']
bev_mapping_vfs = input_dict['bev_mapping_vfs']
these variate were used in your code <vfe.utils.py> class HVFeatureNetFinal's forward function
through pcdet we can transfrom data to bach_dict,which is a dict with 'frame_id','gt_boxes','points','use_lead_xyz','voxels','voxel_coords','voxel_num_points','image_shape','batch_size'
I cant understand what is 'bev_mapping_pvs' and 'bev_mapping_vfs'means
if you see my question,please replay me.thanks!
question about the inference speed
Hi, I finished the model training but failed to get the similar speed result according to paper.
about 20 FPS on a RTX2080ti while the official result is 31 FPS. Do you know why this is?
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