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.