Num training images

[sjg918]

hi. Thank you for your work. I use train, val splits below files.

train.txt val.txt train = 3712 / val = 3769

But when trained using Yolo3D_example, displayed in the terminal:

clean up the recorder directory of /home/user/repository/visualDet3D-master/exp/Mono3D/log/defaultconfig=/home/user/repository/visualDet3D-master/config/config.py -1 number of trained parameters of the model: 58388994 Found evaluate function evaluate_kitti_obj Num training images: 7424 Epoch: 0 | Iteration: 49 | Running loss: 0.84490 | eta:8.21h

Num training images: 7424 is fine?

+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+= And i run imdb_precompute_3d.py, I got the result:

start reading training data training split finished precomputing02s, eta:0.24s, total_objs:[10698], usable_objs:[10054] start reading validation data validation split finished precomputing00s, eta:0.01s, total_objs:[0], usable_objs:[0] Preprocessing finished

this is fine? no vaildation objects -_- myconfig.txt <- my config.py thx.

[Owen-Liuyuxuan]

Yes, the training set will include both the left and right images of the training set, so will double the training set.

In the precomputing for the validation set, I avoid actually reading target objects

[sjg918]

Thank you. Have a nice day. ^^)b