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RGB --> same
depth --> same
depth_normalize --> same
obj_id --> eval ['cat_id_0base'], train data['cat_id']
camK --> same
gt_mask --> same
gt_R --> not used in eval
gt_t --> not used in eval
gt_s --> not used in eval
mean_shape --> not used in eval
gt_2D --> same
sym --> same
def_mask --> eval def_mask=data['roi_mask'], train def_mask=data['roi_mask_deform']
required for eval:
pred_RT --> obtained from line 84, generate_RT([p_green_R_vec, p_red_R_vec], [f_green_R, f_red_R], p_T, mode='vec', sym=sym)
The category id definition is the SAME. The name is changed to remind me that the category id starts from 0.
gt_handle_visibility is manually labelled. I have already uploaded it to this repo.
So for eval a different dataset is used compared to training,
how are the values for the dict obtained?
eval:
train:
RGB --> same
depth --> same
depth_normalize --> same
obj_id --> eval ['cat_id_0base'], train data['cat_id']
camK --> same
gt_mask --> same
gt_R --> not used in eval
gt_t --> not used in eval
gt_s --> not used in eval
mean_shape --> not used in eval
gt_2D --> same
sym --> same
def_mask --> eval def_mask=data['roi_mask'], train def_mask=data['roi_mask_deform']
required for eval:
pred_RT --> obtained from line 84, generate_RT([p_green_R_vec, p_red_R_vec], [f_green_R, f_red_R], p_T, mode='vec', sym=sym)
information not present in GPV Pose --> how to obtain gt_handle_visibility
in mentian/object-deformnet --> https://github.com/mentian/object-deformnet/search?q=gt_handle_visibility
gt_handle_visibility = nocs['gt_handle_visibility']
so my question is why is the category id definition different? and for an own dataset how to obtain the value gt_handle_visibility
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