doc/tutorials/dwx_tutorials_intermediate.md

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# Copyright (c) 2018-2019 NVIDIA CORPORATION.  All rights reserved.

@page intermediate_tutorials Intermediate Tutorials
@tableofcontents

These intermediate tutorials are intended for users already familiar with DriveWorks and are able to build simple applications.<br>
This is a deep dive into most of the functionalities provided, including image and point cloud processing, Deep Neural Networks (DNN) usage,<br>
egomotion and self-calibration.

@section dwx_intermediate_tutorials_sensors Sensor Management

| Tutorial | Description |
|------|-------------|
| @ref sensormanager_usecase1 | Accessing time-sorted stream of events from an aggregate set of sensors. |

**Modules used:** @ref core_mainsection | @ref sensors_mainsection | @ref sensormanager_mainsection | @ref rig_mainsection.
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@section dwx_intermediate_tutorials_ip Image Processing

| Tutorial | Description |
|------|-------------|
| @ref image_usecase5 | Creating and converting images into different formats. |
| @ref imagetransformation_usecase1 | Scaling images. |
| @ref image_usecase2 | Your first image streamer. |
| @ref image_usecase4 | Streaming images between threads. |
| @ref image_usecase3 | Streaming images across processes. |
| @ref image_usecase1 | Capturing images from screen. |
| @ref colorcorrection_usecase1 | Adjusting Color Distribution. |
| @ref connectedcomponents_usecase1 | Applying Component Labeling to Grey Scale Images. |
| @ref rectifier_usecase1 | Converting images to a different camera model. |
| @ref imageprocessing_features_usecase1 | Tracking features across frames. |
| @ref imageprocessing_tracking_usecase1 | Tracking the position and size of features across frames. |
| @ref imageprocessing_tracking_usecase2 | Tracking 2D bounding boxes across frames. |
| @ref stereo_usecase1 | Computing a disparity map from a pair of stereo images. |
| @ref stereo_usecase2 | Computing a disparity map from a pair of stereo images on PVA and NVENC. |
| @ref sfm_usecase1 | Estimating the structure of a scene from camera frames. |
| @ref denseopticalflow_usecase1 | Building a pipeline running on PVA. |
| @ref imageprocessing_geometry_pose_usecase1 | Determines camera pose using PnP pose estimator. |

**Modules used:** @ref image_mainsection | @ref rig_mainsection | @ref colorcorrection_mainsection | @ref connectedcomponents_mainsection | @ref rectifier_mainsection <br> @ref imageprocessing_features_mainsection | @ref imageprocessing_tracking_mainsection | @ref imageprocessing_filtering_mainsection | @ref stereo_mainsection | @ref sfm_mainsection | @ref denseopticalflow_mainsection.
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@section dwx_intermediate_tutorials_pc_processing Point Cloud Processing

| Tutorial | Description |
|------|-------------|
| @ref pointcloudprocessing_usecase1 | Allocating and freeing memory for low level point cloud processing. |
| @ref pointcloudprocessing_usecase2 | Accumulating Lidar spins. |
| @ref pointcloudprocessing_usecase3 | Combining multiple point clouds in the a common coordinate system. |
| @ref pointcloudprocessing_usecase4 | Generating 2D images from accumulated point clouds. |
| @ref pointcloudprocessing_usecase5 | Aligning 3D points from a pair of Lidar spins. |
| @ref pointcloudprocessing_usecase6 | Estimating a 3D plane from a point cloud. |
| @ref pointcloudprocessing_usecase7 | Point cloud filter. |

**Modules used:** @ref pointcloudprocessing_mainsection.
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@section dwx_intermediate_tutorials_vehicle Vehicle Actuation

| Tutorial | Description |
|------|-------------|
| @ref vehicleio_usecase1 | How to actuate a vehicle. |
| @ref egomotion_usecase1 | How to track and predict a vehicle's pose. |

**Modules used:** @ref vehicleio_mainsection | @ref egomotion_mainsection
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@section dwx_intermediate_tutorials_selfcalib Self-Calibration

| Tutorial | Description |
|------|-------------|
| @ref cameramodel_usecase0 | How to perform Ray-to-Pixel and Pixel-to-Ray transformations. |
| @ref calibration_usecase_features | A complete workflow detailing camera self-calibration. |
| @ref calibration_usecase_imu | A complete workflow detailing IMU self-calibration. |
| @ref calibration_usecase_lidar | A complete workflow detailing Lidar self-calibration. |
| @ref calibration_usecase_radar | A complete workflow detailing Radar self-calibration. |
| @ref calibration_usecase_stereo | A complete workflow detailing epi-polar based stereo self-calibration. |
| @ref calibration_usecase_vehicle | A complete workflow detailing steering system properities self-calibration. |

**Modules used:** @ref cameramodel_mainsection | @ref calibration_mainsection.
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@section dwx_intermediate_tutorials_dnn Deep Neural Networks (DNN)

| Tutorial | Description |
|------|-------------|
\if DW
| @ref dataconditioner_usecase1 | Formatting your data. |
| @ref dnn_usecase1 | The DriveWorks DNN framework. |
| @ref dnn_usecase2 | DNN inference using tensors. |
| @ref dnn_usecase3 | DNN inference using safe DLA. |
| @ref clusterer_usecase1 | A DBSCAN implementation. |
\elseif DAV
| @ref drivenet_usecase1 | A deep neural network trained for object detection. |
| @ref openroadnet_usecase1 | A deep neural network trained for freespace detection. |
| @ref mapnet_usecase1 | A deep neural network trained for landmark detection. |
| @ref parknet_usecase1 | A deep neural network trained for parking space detection. |
| @ref pathnet_usecase1 | A deep neural network trained for path detection. |
| @ref pilotnet_usecase1 | A deep neural network trained for predicting paths for maneuvers. |
| @ref signnet_usecase1 | A deep neural network trained for traffic sign classification. |
| @ref lightnet_usecase1 | A deep neural network trained for traffic light classification. |
| @ref clearsightnet_usecase1 | A deep neural network trained for camera occlusion detection. |
\endif
\if DW
**Modules used:** @ref dnn_mainsection | @ref dataconditioner_mainsection | @ref clusterer_mainsection
\elseif DAV
**Modules used:** @ref drivenet_mainsection | @ref openroadnet_mainsection | @ref mapnet_mainsection | @ref pathnet_mainsection | @ref signnet_mainsection | @ref lightnet_mainsection | @ref pathnet_mainsection @ref clearsightnet_mainsection.
\endif