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_dec_infer-resnet_tiled_display_int8.txt: Demonstrates 30 stream decodes with primary inferencing. (For dGPU and Jetson AGX Xavier platforms only.) * source30_1080p_dec_infer-resnet_tiled_display_int8.yml: YAML based config file to demonstrate 30 stream decode with primary inferencing. (For dGPU and Jetson AGX Xavier platforms only.) * source4_1080p_dec_infer-resnet_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_dec_infer-resnet_tracker_sgie_tiled_display_int8.yml: YAML based config file to demonstrate four stream decode with primary inferencing, object tracking, and three different secondary classifiers. (For dGPU and Jetson AGX Xavier platforms only.) * source4_1080p_dec_infer-resnet_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_primary.yml: YAML based config file to configure 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. * config_infer_secondary_carcolor.yml,config_infer_secondary_carmake.yml, config_infer_secondary_vehicletypes.yml: YAML based config file to configure a nvinfer element as secondary classifier. * config_tracker_IOU.yml: Config file for IOU tracker. * config_tracker_NvSORT.yml: Config file for NvSORT tracker. * config_tracker_NvDeepSORT.yml: Config file for NvDeepSORT tracker. * config_tracker_NvDCF_accuracy.yml: Config file for NvDCF tracker for higher accuracy. * config_tracker_NvDCF_max_perf.yml: Config file for NvDCF tracker for max perf mode. * config_tracker_NvDCF_perf.yml: Config file for NvDCF tracker for perf mode. * config_preprocess.txt : Config file for using preprocess in PGIE mode. * config_preprocess_sgie.txt : Config file for using preprocess in SGIE mode. * source4_1080p_dec_preprocess_infer-resnet_preprocess_sgie_tiled_display_int8.txt : Demonstrates four stream decodes with preprocess plugin in PGIE mode followed by primary inferencing, preprocess plugin in SGIE mode, and three different secondary classifiers. (For dGPU and Jetson AGX Xavier platforms only.) * source30_1080p_dec_preprocess_infer-resnet_tiled_display_int8.txt : Demonstrates 30 stream decodes with preprocess plugin in PGIE mode followed by primary inferencing. (For dGPU and Jetson AGX Xavier platforms only.) * sources_30.csv: CSV file for 30 sources required in source30_1080p_dec_infer-resnet_tiled_display_int8.yml. * sources_4.csv: CSV file for 30 sources required in source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.yml. * 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.) * source2_1080p_dec_infer-resnet_demux_int8.txt: Demonstrates demux mode for two sources. * config_mux_source4.txt, config_mux_source30.txt: Sample nvstreammux (new) config files. For more details see :ref:`Section Mux Config Properties `. * 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 ds-triton ``nvinferserver`` config file in the ``[*-gie]`` group of application config file. * source1_primary_detector.txt (Single source + object detection using ssd) * Configuration files for ds-triton ``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) * config_infer_primary_classifier_mobilenet_v1_graphdef.txt (TensorFlow Mobilenet V1 classifier) * config_infer_primary_detector_ssd_mobilenet_v1_coco_2018_01_28.txt (TensorFlow Mobilenet V1 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 ds-triton ``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.mp4 MJPEG containerized stream sample_720p.mp4 Containerized stream sample_cam5.mp4 H264 containerized stream (360D camera stream) sample_cam6.mp4 H264 containerized stream (360D camera stream) sample_industrial.jpg JPEG image yoga.jpg Image for perspective projection in Dewarper yoga.mp4 Containerized stream sample_qHD.mp4 Used for MaskRCNN sample_qHD.h264 H264 elementary stream 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 fisheye_dist.mp4 Containerized stream sonyc_mixed_audio.wav Audio bitstream sample_office.mp4 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 , S * config_tracker_DeepSORT.yml: Config file for DeepSORT tracker. - 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.