i get the above error ,while running the local Video file
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:685 [Implicit Engine Info]: layers num: 3
0 INPUT kFLOAT Input 3x300x300
1 OUTPUT kFLOAT NMS 1x200x7
2 OUTPUT kFLOAT NMS_1 1x1x1
0:00:02.358925785 10933 0x55dc260f7270 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger:<primary-inference> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1806> [UID = 1]: Use deserialized engine model: /home/ubuntu/PoC/model/Primary_Bottle_SSD/ssd_resnet18_retrained_epoch_040_bo_99_bl_94_rej_84.etlt_b1_gpu0_fp32.engine
0:00:02.363315957 10933 0x55dc260f7270 INFO nvinfer gstnvinfer_impl.cpp:313:notifyLoadModelStatus:<primary-inference> [UID 1]: Load new model:PoC_pgie_config.txt sucessfully
Running...
ERROR from element Stream-muxer: Input buffer number of surfaces (1684472064) must be equal to mux->num_surfaces_per_frame (4)
Set nvstreammux property num-surfaces-per-frame appropriately
Error details: gstnvstreammux.c(364): gst_nvstreammux_chain (): /GstPipeline:Bottle-pipeline/GstNvStreamMux:Stream-muxer
END Running...===========
Please provide the following information when requesting support.
• Hardware (T4/V100/Xavier/Nano/etc) ==> T4
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc)
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)