PGIE element could not be created. Exiting

Please provide complete information as applicable to your setup.

**• Hardware Platform (Jetson / GPU)**GPU3080
• DeepStream Version6.3
I tried to run deepstream-pose-classification using triton version app.
But the app failed as
PGIE element could not be created. Exiting.
What could be wrong?

The config files are as follows

deepstream_pose_classification_config.yaml

source-list:
   list: file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_walk.mov

streammux:
  width: 1280
  height: 720
  batched-push-timeout: 40000

tracker:
  enable: 1
  ll-lib-file: /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
  ll-config-file: /opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_tracker_NvDCF_accuracy.yml

primary-gie:
  plugin-type: 1
  #config-file-path: ../nvinfer/peoplenet_tao/config_infer_primary_peoplenet.txt
  config-file-path: ../triton/peoplenet_tao/config_infer_primary_peoplenet.yml
  #config-file-path: ../triton-grpc/peoplenet_tao/config_infer_primary_peoplenet.yml

secondary-gie0:
  plugin-type: 1
  #config-file-path: ../nvinfer/bodypose3d_tao/config_infer_secondary_bodypose3dnet.txt
  config-file-path: ../triton/bodypose3d_tao/config_infer_secondary_bodypose3dnet.yml
  #config-file-path: ../triton-grpc/bodypose3d_tao/config_infer_secondary_bodypose3dnet.yml

secondary-preprocess1:
  config-file-path: ../nvinfer/bodypose_classification_tao/config_preprocess_bodypose_classification.txt

secondary-gie1:
  plugin-type: 2
  #config-file-path: ../nvinfer/bodypose_classification_tao/config_infer_third_bodypose_classification.txt
  config-file-path: ../triton/bodypose_classification_tao/config_infer_third_bodypose_classification.txt
  #config-file-path: ../triton-grpc/bodypose_classification_tao/config_infer_third_bodypose_classification.yml

sink:
  #0 fakesink 
  #1 filesinke generate the out.mp4 file in the current directory
  #2 rtspsink publish at rtsp://localhost:8554/ds-test
  #3 displaysink
  sink-type: 3

config_infer_primary_peoplenet.yml

infer_config {
  unique_id: 1
  gpu_ids: [0]
  max_batch_size: 1
  backend {
    inputs: [ {
      name: "input_1"
    }]
    outputs: [
      {name: "output_bbox/BiasAdd"},
      {name: "output_cov/Sigmoid"}
    ]
    triton {
      model_name: "peoplenet"
      version: -1
      model_repo {
        root: "../../../models"
        strict_model_config: true
      }
    }
  }

  preprocess {
    network_format: MEDIA_FORMAT_NONE
    tensor_order: TENSOR_ORDER_LINEAR
    tensor_name: "input_1"
    maintain_aspect_ratio: 0
    frame_scaling_hw: FRAME_SCALING_HW_DEFAULT
    frame_scaling_filter: 1
    normalize {
      scale_factor: 0.0039215697906911373
      channel_offsets: [0, 0, 0]
    }
  }

  postprocess {
    labelfile_path: "../../../models/peoplenet/labels.txt"
    detection {
      num_detected_classes: 1
      per_class_params {
        key: 0
        value { pre_threshold: 0.4 }
      }
      nms {
        confidence_threshold:0.2
        topk:20
        iou_threshold:0.5
      }
    }
  }

  extra {
    copy_input_to_host_buffers: false
    output_buffer_pool_size: 2
  }
}
input_control {
  process_mode: PROCESS_MODE_FULL_FRAME
  operate_on_gie_id: -1
  interval: 0
}

config_infer_secondary_bodypose3dnet.yml

infer_config {
  unique_id: 1
  gpu_ids: 0
  max_batch_size: 8
  backend {
    inputs: [ 
      {name: "input0"},
      {name: "k_inv"},
      {name: "t_form_inv"},
      {name: "scale_normalized_mean_limb_lengths"},
      {name: "mean_limb_lengths"}
    ]
    outputs: [
      {name: "pose2d"},
      {name: "pose2d_org_img"},
      {name: "pose25d"},
      {name: "pose3d"}
    ]
    triton {
      model_name: "bodypose3dnet"
      version: -1
      model_repo {
        root: "../../../models"
        strict_model_config: true
      }
    }
    output_mem_type: MEMORY_TYPE_DEFAULT
  }

  preprocess {
    network_format: IMAGE_FORMAT_BGR
    tensor_order: TENSOR_ORDER_LINEAR
    maintain_aspect_ratio: 0
    symmetric_padding: 0
    frame_scaling_hw: FRAME_SCALING_HW_DEFAULT
    frame_scaling_filter: 1
    normalize {
      scale_factor: 0.00392156
    }
  }
  postprocess {
    other {}
  }

  custom_lib {
    path: "../../../apps/tao_others/deepstream-pose-classification/nvdsinfer_custom_impl_BodyPose3DNet/libnvdsinfer_custom_impl_BodyPose3DNet.so"
  }

  extra {
    copy_input_to_host_buffers: false
    output_buffer_pool_size: 64
  }
}

input_control {
  process_mode: PROCESS_MODE_CLIP_OBJECTS
  operate_on_gie_id: 1
  operate_on_class_ids: [0]
  interval: 0
}

output_control {
  output_tensor_meta: true
}

config_infer_third_bodypose_classification.yml


infer_config {
  unique_id: 4
  gpu_ids: 0
  max_batch_size: 1
  backend {
    triton {
      model_name: "poseclassificationnet"
      version: -1
      model_repo {
        root: "../../../models"
        strict_model_config: true
      }
    }
    output_mem_type: MEMORY_TYPE_DEFAULT
  }

  input_tensor_from_meta {
    is_first_dim_batch: true
  }

  postprocess {
    classification {
      custom_parse_classifier_func: "NvDsParseCustomPoseClassification"
      threshold: 0.51
    }
  }

  custom_lib {
    path: "../../../apps/tao_others/deepstream-pose-classification/infer_pose_classification_parser/libnvdsinfer_pose_classfication_parser.so"
  }

  extra {
    output_buffer_pool_size: 4
  }
}

output_control {
  output_tensor_meta: true
}

You can export GST_DEBUG=5 and run the pipeline. maybe you will see the error.

Do I need docker to run triton version?

Docker Containers — DeepStream documentation 6.4 documentation You can try deepstream container with Triton installed. If you installed triton server, maybe you can set ENV GST_DEBUG to see the error

If you want to run inference in triton, it is recommended that you use the following image

nvcr.io/nvidia/deepstream:6.3-gc-triton-devel

thanks let me try

There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks

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