Sample Configurations and Streams

Contents of the package

This section provides information about included sample configs and streams.

• samples: Directory containing sample configuration files, streams, and models to run the sample applications.

• samples/configs/deepstream-app: Configuration files for the reference application:

  • source30_1080p_resnet_dec_infer_tiled_display_int8.txt: Demonstrates 30 stream decodes with primary inferencing. (For dGPU and Jetson AGX Xavier platforms only.)

  • source30_1080p_dec_preprocess_infer-resnet_tiled_display_int8.txt: Demonstrates 30 stream decodes with primary inferencing on preprocessed ROIs. (For dGPU and Jetson AGX Xavier platforms only.)

  • source4_1080p_resnet_dec_infer_tiled_display_int8.txt: Demonstrates four stream decodes with primary inferencing, object tracking, and three different secondary classifiers. (For dGPU and Jetson AGX Xavier platforms only.)

  • source4_1080p_resnet_dec_infer_tracker_sgie_tiled_display_int8_gpu1.txt: Demonstrates four stream decodes with primary inferencing, object tracking, and three different secondary classifiers on GPU 1 (for systems that have multiple GPU cards). For dGPU platforms only.

  • config_infer_primary.txt: Configures a nvinfer element as primary detector.

  • config_infer_secondary_carcolor.txt, config_infer_secondary_carmake.txt, config_infer_secondary_vehicletypes.txt: Configure a nvinfer element as secondary classifier.

  • iou_config.txt: Configures a low-level IOU (Intersection over Union) tracker.

  • tracker_config.yml: Configures the NvDCF tracker.

  • source1_usb_dec_infer_resnet_int8.txt: Demonstrates one USB camera as input.

  • source1_csi_dec_infer_resnet_int8.txt: Demonstrates one CSI camera as input; for Jetson only.

  • source2_csi_usb_dec_infer_resnet_int8.txt: Demonstrates one CSI camera and one USB camera as inputs; for Jetson only.

  • source6_csi_dec_infer_resnet_int8.txt: Demonstrates six CSI cameras as inputs; for Jetson only.

  • source8_1080p_dec_infer-resnet_tracker_tiled_display_fp16_nano.txt: Demonstrates 8 Decode + Infer + Tracker; for Jetson Nano only.

  • source8_1080p_dec_infer-resnet_tracker_tiled_display_fp16_tx1.txt: Demonstrates 8 Decode + Infer + Tracker; for Jetson TX1 only.

  • source12_1080p_dec_infer-resnet_tracker_tiled_display_fp16_tx2.txt: Demonstrates 12 Decode + Infer + Tracker; for Jetson TX2 only.

  • source2_1080p_dec_infer-resnet_demux_int8.txt: Demonstrates demux mode for two sources.

• samples/configs/deepstream-app-triton: Configuration files for the reference application for inferencing using Triton Inference Server.

• source30_1080p_dec_infer-resnet_tiled_display_int8.txt (30 Decode + Infer)

• source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt (4 Decode + Infer + SGIE + Tracker)

• source1_primary_classifier.txt (Single source + full frame classification)

Note

Other classification models can be used by changing the nvinferserver config file in the [*-gie] group of application config file.

• source1_primary_detector.txt (Single source + object detection using ssd)

• Configuration files for nvinferserver element in configs/deepstream-app-triton/

  • config_infer_plan_engine_primary.txt (Primary Object Detector)

  • config_infer_secondary_plan_engine_carcolor.txt (Secondary Car Color Classifier)

  • config_infer_secondary_plan_engine_carmake.txt (Secondary Car Make Classifier)

  • config_infer_secondary_plan_engine_vehicletypes.txt (Secondary Vehicle Type Classifier)

  • config_infer_primary_classifier_densenet_onnx.txt (DenseNet-121 v1.2 classifier)

  • config_infer_primary_classifier_inception_graphdef_postprocessInTriton.txt (TensorFlow Inception v3 classifier - Post processing in Triton)

  • config_infer_primary_classifier_inception_graphdef_postprocessInDS.txt (TensorFlow Inception v3 classifier - Post processing in DeepStream)

  • config_infer_primary_detector_ssd_inception_v2_coco_2018_01_28.txt (TensorFlow SSD Inception V2 Object Detector)

• samples/configs/deepstream-app-triton-grpc: Configuration files for the reference application for inferencing using Triton Inference Server gRPC

• source30_1080p_dec_infer-resnet_tiled_display_int8.txt (30 Decode + Infer)

• source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt (4 Decode + Infer + SGIE + Tracker)

• Configuration files for nvinferserver element in configs/deepstream-app-triton-grpc/

  • config_infer_plan_engine_primary.txt (Primary Object Detector)

  • config_infer_secondary_plan_engine_carcolor.txt (Secondary Car Color Classifier)

  • config_infer_secondary_plan_engine_carmake.txt (Secondary Car Make Classifier)

  • config_infer_secondary_plan_engine_vehicletypes.txt (Secondary Vehicle Type Classifier)

• NVIDIA TAO Toolkit pretrained Models:

  • samples/configs/tao_pretrained_models: Contains README.md to obtain configs and models for TAO toolkit.

• samples: Directory containing sample configuration files, models, and streams to run the sample applications.

• samples/streams: The following streams are provided with the DeepStream SDK:

  Streams	Type of Stream
  sample_1080p_h264.mp4	H264 containerized stream
  sample_1080p_h265.mp4	H265 containerized stream
  sample_720p.h264	H264 elementary stream
  sample_720p.jpg	JPEG image
  sample_720p.mjpeg	MJPEG stream
  sample_cam6.mp4	H264 containerized stream (360D camera stream)
  sample_industrial.jpg	JPEG image
  yoga.jpg	Image for perspective projection in Dewarper
  sample_qHD.mp4	Used for MaskRCNN
  sample_push.mov	H264 containerized stream
  sample_ride_bike.mov	H264 containerized stream
  sample_run.mov	H264 containerized stream
  sample_walk.mov	H264 containerized stream

• samples/models: The following sample models are provided with the SDK:

DeepStream Reference application

Model	Model Type	No. of Classes	Resolution
Primary Detector	Resnet10	4	640 × 368
Secondary Car Color Classifier	Resnet18	12	224 × 224
Secondary Car Make Classifier	Resnet18	6	224 × 224
Secondary Vehicle Type Classifier	Resnet18	20	224 × 224

Segmentation example

Model	Model Type	No. of Classes	Resolution
Industrial	Resnet18 + UNet	1	512 x 512
Semantic	Resnet18 + UNet	4	512 x 512
Instance	Resnet50 + Maskrcnn	2	1344 x 832

Scripts included along with package

The following scripts are included along with the sample applications package:

• samples/ prepare_classification_test_video.sh: Downloads Imagenet test images and creates a video out of it to test with Classification models like TensorFlow Inception, ONNX DenseNet etc.

• samples/ prepare_ds_triton_model_repo.sh: Prepare the Model repository for Triton Inference Server

  1. Creates engine files for Caffe and UFF based models provided as part of SDK.

  2. Downloads Model files for ONNX DenseNet , SSD Inception V2 Coco, Inception v3.

  For additional information on the above models, refer to:

  • ONNX DenseNet - https://github.com/onnx/models/tree/master/vision/classification/densenet-121

  • SSD Inception V2 Coco - https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md

  • Inception V3 - https://github.com/tensorflow/models/tree/master/research/slim

• uninstall.sh: Used to clean up previous DS installation.