Assertion Error when training BodyPoseNet with my custom data

• Network Type : BodyPoseNet

When I try to training BodyPoseNet with my custom data, the assertion error occurs. Before that, the first error is like this

tensorflow.python.framework.errors_impl.InvalidArgumentError: Dimensions must be equal, but are 180 and 64 for 'Loss/sub' (op: 'Sub') with input shapes: [8,180,102,19], [8,64,36,19].

So I think, I have to change target_shape in bpnet_train_m1_coco_custom.yaml which I wrote [64, 36].
But when I change it to [180,102], the assertion error occurs

INFO    2023-02-06 02:28:14,255| iva.common.logging.logging: Log file already exists at /workspace/tao-experiments/bpnet/models/custom_v1/status.json
Traceback (most recent call last):
  File "</usr/local/lib/python3.6/dist-packages/driveix/bpnet/scripts/>", line 3, in <module>
  File "<frozen driveix.bpnet.scripts.train>", line 221, in <module>
  File "<frozen driveix.bpnet.scripts.train>", line 150, in main
  File "<frozen moduluspy.modulus.modulusobject.modulusobject>", line 158, in deserialize_maglev_object
  File "<frozen moduluspy.modulus.modulusobject.modulusobject>", line 145, in _deserialize_recursively
  File "<frozen moduluspy.modulus.modulusobject.modulusobject>", line 167, in deserialize_maglev_object
  File "<frozen moduluspy.modulus.modulusobject.modulusobject>", line 432, in wrapper
  File "<frozen driveix.bpnet.dataloaders.bpnet_dataloader>", line 150, in __init__
  File "<frozen driveix.bpnet.dataloaders.processors.label_processor>", line 57, in __init__
Telemetry data couldn't be sent, but the command ran successfully.
[WARNING]: <urlopen error [Errno -2] Name or service not known>
Execution status: FAIL

It only says “Assertion Error” so I don’t know what to do. Please help me to solve this problem. (Is there a possibility that the train-fold file was made incorrectly?)

From Body Pose Estimation — TAO Toolkit 4.0 documentation

  • Currently, BodyPoseNet only supports the given default skeleton configuration at pose_config_path. The inference pipelines do not support custom skeleton configuration at the moment.

Please check.

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