After setting like this,
I have a question about the output output when executing the "python run/train_3d.py --cfg configs/panoptic/resnet50/prn64_cpn80x80x20_960x512_cam5.yaml" command.
Why are there no results for all val data?
(There are only 10 validation results in output/.../image_with_joints/
validation_0000000_view_1_gt ~ validation_0000000_view_5_gt
validation_0000002_view_1_gt ~ validation_0000002_view_5_gt)
Following the git description, the directory tree was configured as follows.
${POSE_ROOT} |-- models | |-- pose_resnet50_panoptic.pth.tar |-- data |-- panoptic-toolbox |-- data |-- 171204_pose1 | |-- hdImgs | |-- hdvideos | |-- hdPose3d_stage1_coco19 | |-- calibration_160224_haggling1.json |-- 171204_pose1_sample
|-- ...
(Due to capacity issues, the 171204_pose1 and 171204_pose1_sample data was used}
After configuring the directory tree, the panoptic.py code is modified as follows.
TRAIN_LIST = [ '171204_pose1', ] VAL_LIST = [ '171204_pose1_sample' ]
After setting like this, I have a question about the output output when executing the "python run/train_3d.py --cfg configs/panoptic/resnet50/prn64_cpn80x80x20_960x512_cam5.yaml" command.
Why are there no results for all val data? (There are only 10 validation results in output/.../image_with_joints/ validation_0000000_view_1_gt ~ validation_0000000_view_5_gt validation_0000002_view_1_gt ~ validation_0000002_view_5_gt)