Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU): GPU
• DeepStream Version: 6.0
We have a dual encoder semantic segmentation model which takes 2 inputs (each an RGB image) loaded using nvinfer and we are trying to provide input to it.
We are trying to create our own custom tensor through nvdspreprocess and provide it to nvinfer. This custom tensor should consist of the two (RGB) input images stacked along the channel dimension (size: 1x6xHxW). To test capability, in nvdspreprocess configuration we set the tensor dimensions to 1x6xHxW.
However, we’re getting the error “RGB/BGR input format specified but network input channels is not 3 normalization_mean_subtraction_impl_initialize failed”, which tells me that we cannot set the tensor’s number of channels to any number more than 3, am I correct? If yes, what would be other ways to create a 6 channel tensor and send it to nvinfer? Or possibly, provide 2 RGB frames to nvinfer as input instead of one?