Please provide the following information when requesting support.
detectnet_v2_train_peoplenet_r34_3C.txt (5.3 KB)
• Hardware (T4/V100/Xavier/Nano/etc) - XavierNX
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc) - Detectnet_v2
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here) - 3.22.02
Hello everyone,
I was training an object detection model using mobilenet_v2 as the architecture. I would like to know why the load_graph
option does not work when training the network. In the 1st run of training if I set the load_graph = True
, then I get the error saying - layer output_cov not defined (Not sure whether this is the name but the error is very similar to this)
If I set the load_graph = False
then I get no error when I start the training. But on the other hand, I suspect that the pre-trained weights are not loaded. However, when I set the first_validation _epoch = 1
, then I get mAP as 0 for all the classes.
Following is the spec file I am using for training mobilenet_v2:
detectnet_v2_train_peoplenet_mv2_3C.txt (5.2 KB)
If I use resnet34 as the architecture and set load_graph = True
, the pre-trained weights are loaded in the 1st run of training. I do not have any error and the result for the first_validation _epoch = 1
is mAP value of 28.3.
Following is the spec file I am using for training resnet34:
detectnet_v2_train_peoplenet_r34_3C.txt (5.3 KB)
I would like to know this difference in behavior when using mobilenet_v2 and resnet34 and the possible solution.
Looking forward to your replies !!
Thanks