5.2. Release notes - 09_02_00

5.2.1. Features

Note

New features vs previous release are marked in bold

5.2.1.1. Hardware support

  1. J722S HS support

  2. Fusion1 RevC daughter card with UB960 FPDLink deserializer

  3. IMX390 2MP CSI2 image sensor + UB953 FPDLink serializer

  4. AR0233 2.5MP CSI2 image sensor + UB953 FPDLink serializer

  5. AR0820 8MP CSI2 image sensor + UB953 FPDLink serializer

5.2.1.2. Software features

Important

Below is a summary of key features. Refer individual SDK Components release notes for more details

5.2.1.2.1. Edge AI TIOVX Apps

  • TI OpenVx based application for demonstrating DL inference with multiple input and output sources

    • Single input Single inference dataflow

    • Single input Multi-network inference dataflow

    • Multi input Multi-network dataflow

    • Supports all models (Classification, Detection, Segmentation) from Edge AI Model Zoo

    • Agnostic to DL runtime, runs purely using TIDL OpenVx Node

    • Optimal dataflows with RTOS based camera and display OpenVx nodes

    • Optimal dataflows with V4L2 based decoder and encoder accelerators with zero-buffer-copy overheads

    • ARM NEON based SIMD optimized pre/post processing kernels

  • Refer to Edge AI TIOVX Apps Reference Guides for further details

5.2.1.2.2. Vision Apps (ADAS, Vision, DL demos)

  • OpenVX based demos for ADAS, Vision, deep learning applications

    • FreeRTOS on C7x, R5F and Linux/QNX on A53

    • Integrates all major PSDK RTOS and PSDK LINUX SW components like TIDL, MMALIB, MCU+ SDKs, OpenVX, C7x algorithms, imaging/sensors, IPC, Linux, FreeRTOS, SPL/uboot.

    • Integrates all major HW components like CSI2 camera, HDMI display, UART, I2C, ethernet, SD card

  • Deep Learning demos

    • Image Classification demo

      • File based

      • Camera based

    • Debug support for the ability to debug intermediate layer information from TIDL node

  • ADAS/Vision demos

    • Dense optical flow (DOF) demo

    • Stereo disparity engine demo

    • Single and multi camera to display (CSI2RX + VISS + LDC + MSC + Display) demo

    • C7x algorithm offload demo

  • OpenVX target nodes

    • image post-processing and visualization nodes for DOF, Stereo demos

  • Profiling, logging and other utility APIs

  • All included MCU tasks are running on MCU2_0 (VPAC HWA)

5.2.1.2.3. MCU-PLUS-SDK

  • RTOS device drivers running on R5F, C7x

Refer to MCU-PLUS-SDK release notes LINK for more details.

5.2.1.2.4. TI Deep learning Product (TIDL) and MMALIB

  • TensorFlow Lite Runtime with Delegate API support for heterogeneous execution on ARM+C7x_MMA

  • ONNX Runtime with Execution Provider support for heterogeneous execution on ARM+C7x_MMA

  • NEO-AI-DLR support - TVM model compilation for heterogeneous execution on ARM+C7x_MMA

  • TIDL deep learning inference engine library running on C7x/MMA

  • Supports Caffe, ONNX, TFlite network exchange formats

  • Supported layers: Convolution, Deconvolution, Pooling, ReLU, Elt-wise, Inner product, Soft-max, and many more

  • TIDL network import tool and graph visualizer tool

  • Post Training Quantization options for 8-bit, 16-bit and mixed precision inference

  • Support for batch processing

  • Support for auto C7x code generation with TVM

  • Refer to edgeai-tidl-tools for further details

5.2.1.2.5. TI OpenVX (TIOVX)

  • OpenVX v1.1 compliant implementation with graph pipelining, user data object, bidirectional parameters and safe casts extensions support

  • OpenVX API on A53 running Linux/QNX

  • OpenVX target kernels on C7x, R5F, A53

  • OpenVX v1.1 C6x optimized kernels recompiled for C7x

  • OpenVX nodes for

    • TIDL (C7x-MMA)

    • VISS (R5F)

    • LDC (R5F)

    • MSC (multi-scalar) (R5F)

    • Pyramid (using MSC) (R5F)

    • Dense Optical Flow (R5F)

    • Stereo Disparity Engine (R5F)

    • CSI2-RX camera (R5F)

    • CSI2-TX (R5F)

    • Display (HDMI) (R5F)

  • OpenVX tutorials for getting started

  • PyTIOVX tools for target kernel code generation

  • Performance Analyzer tool for run time logging of OpenVX graphs

  • VISS node supports heterogeneous cameras

5.2.1.2.6. Imaging

  • IMX390 2MP sensor driver (30/60fps) with IQ tuning

  • AR0233 2.5MP sensor driver with IQ tuning

  • AR0820 8MP sensor driver with IQ tuning

  • TI Auto-exposure and auto white-balance algorithms

  • Support for UB960 broadcast mode

  • Sensor framework supports heterogeneous cameras

5.2.1.2.7. TI Autonomous Driving Algorithms (TIADALG)

  • Image pre-processing APIs for color plane conversion and separation YUV to RGB for DL applications (C6x optimized. recompiled for C7x)

  • Camera Pose estimation API using solve pnp technique (C6x optimized. recompiled for C7x)

  • Visual localization algorithm (C6x optimized. recompiled for C7x)

  • Structure from Motion algorithm

5.2.1.2.8. FreeRTOS

  • FreeRTOS for R5F and C7x

5.2.1.2.9. Code Gen Tools (CGT)

  • TI Compiler, assembler, linker for R5F, C7x

  • TI LLVM (CLANG) Compiler, assembler, linker for R5F

  • GCC compiler for A53 (needs to be downloaded separately)

5.2.2. Device Support and Validation Information

SoC

Build Host (OS)

Run Target (OS)

Test Plaform

J722S

x86_64 (Linux Ubuntu 22.04)

R5F, C7x running FreeRTOS

A53 running Linux or QNX

J722S EVM with daughter cards

PC emulation mode (1)

x86_64 (Linux Ubuntu 22.04)

x86_64 (Linux Ubuntu 22.04)

x86_64 (Linux Ubuntu 22.04)

(1) Requires download of addon package from mySecure Software

5.2.3. Upgrade and Compatibility

In this section, we only highlight a few significant changes in this SDK. For full list of upgrade and compatibility topics, please refer to individual components release notes SDK Components.

5.2.4. Known Issues

Refer to individual SDK Components release notes for known issues in each component

5.2.5. Change Requests

ID

Head Line

Original Fix Version

New Fix Version

Components

NA

First release of PSDK RTOS on J722S SoC

5.2.5.1. Errata workarounds

None

5.2.6. Additional Reports

For additional reports like test report, traceability refer [LINK] (or ${PSDK RTOS_PATH}/psdk_rtos/docs/additional_reports in package)