Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) Jetson
• DeepStream Version 6.3
• JetPack Version (valid for Jetson only) 5.1.1
• TensorRT Version 8.5.2
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs) Questions
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)
Hi, I am running a DeepStream Pose Classification pipeline on Jetson device. I tested it on tons of videos . For every video the prediction is always "Walking irrespective of the person performing any other activity ( For eg - Sitting, Standing).
I have even tried to change the value of frame-sequence-length starting from min value of 3 to max value of 300 in steps of 10 in config_preprocess_bodypose_classification.txt. Even though after testing it for difference sequence the prediction is always walking.
[user-configs]
#actual sequence length of frames
frames-sequence-length=300
I am attaching the snapshot of the video in which person is sitting for entire video. Even though for this video the prediction is walking with around 70% confidence.
Q1. Can Anyone Let me know what are configurable parameters in the DeepStream PoseClassification Pipeline which would help to achieve the desired accuracy as it is mentioned on the Pose Classification NGC Catalog ?https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/models/poseclassificationnet
Q2 When we had clearly mentioned frame-sequence-length to be of N frames ( N can be 30. 60, 90 etc till max 300). Then why are predicitions happening for every frame instead of happening for set of frames as mentioned in frame-sequence-length?
6 posts - 3 participants