የቴክሳስ መሣሪያዎች AM6x የበርካታ ካሜራ የተጠቃሚ መመሪያን ማዳበር

የደህንነት ክትትል; Enhances surveillance coverage, object tracking, and recognition accuracy.
ዙሪያ View: Enables stereo vision for tasks like obstacle detection and object manipulation.

የካቢን መቅጃ እና የካሜራ መስታወት ስርዓት፡ የተራዘመ ሽፋን ይሰጣል እና ዓይነ ስውር ቦታዎችን ያስወግዳል.
የሕክምና ምስል; Offers enhanced precision in surgical navigation and endoscopy.

ድሮኖች እና የአየር ላይ ምስል; Capture high-resolution images from different angles for various applications.

Connecting Multiple CSI-2 Cameras to the SoC:
To connect multiple CSI-2 cameras to the SoC, follow the guidelines provided in the user manual. Ensure proper alignment and connection of each camera to the designated ports on the SoC.

የመተግበሪያ ማስታወሻ
በ AM6x ላይ ባለብዙ ካሜራ መተግበሪያዎችን ማዳበር

Jianzhong Xu, Qutaiba Saleh

አብስትራክት
This report describes application development using multiple CSI-2 cameras on the AM6x family of devices. A reference design of object detection with deep learning on 4 cameras on the AM62A SoC is presented with performance analysis. General principles of the design apply to other SoCs with a CSI-2 interface, such as AM62x and AM62P.

መግቢያ

በዘመናዊ የእይታ ስርዓቶች ውስጥ የተካተቱ ካሜራዎች ትልቅ ሚና ይጫወታሉ። በአንድ ስርዓት ውስጥ ብዙ ካሜራዎችን መጠቀም የእነዚህን ስርዓቶች አቅም ያሰፋዋል እና በአንድ ካሜራ የማይቻሉ ችሎታዎችን ያስችላል። ከዚህ በታች አንዳንድ የቀድሞ ናቸውamples of applications using multiple embedded cameras:

የደህንነት ክትትል፡ በስትራቴጂያዊ መንገድ የተቀመጡ በርካታ ካሜራዎች አጠቃላይ የስለላ ሽፋን ይሰጣሉ። ፓኖራሚክን ያነቃሉ። views, reduce blind spots, and enhance the accuracy of object tracking and recognition, improving overall security measures.
ዙሪያ View: Multiple cameras are used to create a stereo vision setup, enabling three-dimensional information and the estimation of depth. This is crucial for tasks such as obstacle detection in autonomous vehicles, precise object manipulation in robotics, and enhanced realism of augmented reality experiences.

Cabin Recorder and Camera Mirror System: A car cabin recorder with multiple cameras can provide more coverage using a single processor. Similarly, a camera mirror system with two or more cameras can expand the driver’s field of view እና ከመኪናው አቅጣጫ ሁሉ ዓይነ ስውር ቦታዎችን ያስወግዱ።
Medical Imaging: Multiple cameras can be used in medical imaging for tasks like surgical navigation, providing surgeons with multiple perspectives for enhanced precision. In endoscopy, multiple cameras enable a thorough examination of internal organs.

Drones and Aerial Imaging: Drones often come equipped with multiple cameras to capture high-resolution images or videos from different angles. This is useful in applications like aerial photography, agriculture monitoring, and land surveying.
With the advancement of microprocessors, multiple cameras can be integrated into a single System-on-Chip.
(SoC) to provide compact and efficient solutions. The AM62Ax SoC, with high-performance video/vision processing and deep learning acceleration, is an ideal device for the above-mentioned use cases. Another AM6x device, the AM62P, is built for high-performance embedded 3D display applications. Equipped with 3D graphics acceleration, the AM62P can easily stitch together the images from multiple cameras and produce a high-resolution panoramic view. የ AM62A/AM62P SoC ፈጠራ ባህሪያት እንደ [4]፣ [5]፣ [6]፣ ወዘተ ባሉ የተለያዩ ህትመቶች ላይ ቀርበዋል። ይህ የመተግበሪያ ማስታወሻ እነዚያን የባህሪ መግለጫዎች አይደግምም ይልቁንም ብዙ CSI-2 ካሜራዎችን በ AM62A/AM62P ላይ ወደተከተቱ የእይታ መተግበሪያዎች በማዋሃድ ላይ ያተኩራል።

ሠንጠረዥ 1-1 የምስል ሂደትን በተመለከተ በ AM62A እና AM62P መካከል ያሉትን ዋና ዋና ልዩነቶች ያሳያል።

ሠንጠረዥ 1-1. በምስል ሂደት ውስጥ በ AM62A እና AM62P መካከል ያሉ ልዩነቶች

ሶሲ	AM62A	AM62 ፒ
የሚደገፍ የካሜራ አይነት	With or without a built-in ISP	አብሮ በተሰራው አይኤስፒ
የካሜራ ውፅዓት ውሂብ	ጥሬ/YUV/RGB	YUV/RGB
አይኤስፒ HWA	አዎ	አይ
ጥልቅ ትምህርት HWA	አዎ	አይ
3-D ግራፊክስ HWA	አይ	አዎ

በርካታ CSI-2 ካሜራዎችን ከሶሲ ጋር በማገናኘት ላይ
በምስል 6-2 ላይ እንደሚታየው በ AM1x SoC ላይ ያለው የካሜራ ንዑስ ስርዓት የሚከተሉትን ክፍሎች ይዟል።

MIPI D-PHY Receiver: receives video streams from external cameras, supporting up to 1.5 Gbps per data lane for 4 lanes.

CSI-2 Receiver (RX): receives video streams from the D-PHY receiver and either directly sends the streams to the ISP or dumps the data to DDR memory. This module supports up to 16 virtual channels.
SHIM: a DMA wrapper that enables sending the captured streams to memory over DMA. Multiple DMA contexts can be created by this wrapper, with each context corresponding to a virtual channel of the CSI-2 Receiver.

Multiple cameras can be supported on the AM6x through the use of virtual channels of CSI-2 RX, even though there is only one CSI-2 RX interface on the SoC. An external CSI-2 aggregating component is needed to combine multiple camera streams and send them to a single SoC. Two types of CSI-2 aggregating solutions can be used, described in the following sections.

CSI-2 Aggregator Using SerDes
የበርካታ የካሜራ ዥረቶችን የማጣመር አንዱ መንገድ ተከታታይነት እና ማጥፋት (SerDes) መፍትሄን መጠቀም ነው። ከእያንዳንዱ ካሜራ የሚገኘው የCSI-2 መረጃ በሴሪያላይዘር ተቀይሮ በኬብል ይተላለፋል። ዲሴሪያላይዘር ከኬብሎች የተላለፈውን ሁሉንም ተከታታይ መረጃዎች ይቀበላል (በካሜራ አንድ ገመድ) ፣ ዥረቶቹን ወደ CSI-2 ውሂብ ይለውጣል እና ከዚያ የተጠላለፈ CSI-2 ዥረት ወደ ነጠላ CSI-2 RX በይነገጽ በ SoC ላይ ይልካል። እያንዳንዱ የካሜራ ዥረት በልዩ ምናባዊ ቻናል ተለይቷል። ይህ የማጠቃለያ መፍትሔ ከካሜራዎች እስከ 15 ሜትር የሚደርስ የርቀት ግንኙነት ከሶሲ ጋር የመፍቀድ ተጨማሪ ጥቅም ይሰጣል።

በ AM3x ሊኑክስ ኤስዲኬ የሚደገፉት FPD-Link ወይም V6-Link serializers እና deserializers (SerDes)፣ለዚህ አይነት የCSI-2 ድምር መፍትሄ በጣም ታዋቂ ቴክኖሎጂዎች ናቸው። ሁለቱም FPD-Link እና V3-Link deserializers ሁሉንም ካሜራዎች ለማመሳሰል የፍሬም ማመሳሰል ምልክቶችን ለመላክ የሚያገለግሉ የኋላ ቻናሎች አሏቸው [7]።
ምስል 2-2 አንድ የቀድሞ ያሳያልampብዙ ካሜራዎችን ከአንድ AM6x SoC ጋር ለማገናኘት SerDes ን መጠቀም።

አንድ የቀድሞample of this aggregating solution can be found in the Arducam V3Link Camera Solution Kit. This kit has a deserializer hub which aggregates 4 CSI-2 camera streams, as well as 4 pairs of V3link serializers and IMX219 cameras, including FAKRA coaxial cables and 22-pin FPC cables. The reference design discussed later is built on this kit.

CSI-2 Aggregator without Using SerDes
የዚህ አይነት ሰብሳቢ ከበርካታ MIPI CSI-2 ካሜራዎች ጋር በቀጥታ በመገናኘት ከሁሉም ካሜራዎች የተገኘውን መረጃ ወደ አንድ የCSI-2 የውጤት ዥረት ማጠቃለል ይችላል።

ምስል 2-3 አንድ የቀድሞ ያሳያልample of such a system. This type of aggregating solution does not use any serializer/deserializer but is limited by the maximum distance of CSI-2 data transfer, which is up to 30cm. The AM6x Linux SDK does not support this type of CSI-2 aggregator

በሶፍትዌር ውስጥ በርካታ ካሜራዎችን ማንቃት

Camera Subsystem Software Architecture
ምስል 3-1 የካሜራ ቀረጻ ስርዓት ሶፍትዌር በከፍተኛ ደረጃ የማገጃ ዲያግራም በ AM62A/AM62P ሊኑክስ ኤስዲኬ ያሳያል፣ ይህም በስእል 2-2 ካለው የHW ስርዓት ጋር ይዛመዳል።

ይህ የሶፍትዌር አርክቴክቸር በስእል 2-2 እንደሚታየው ሶሲ ብዙ የካሜራ ዥረቶችን በሴርዴስ አጠቃቀም እንዲቀበል ያስችለዋል። FPD-Link/V3-Link SerDes ለእያንዳንዱ ካሜራ ልዩ የሆነ I2C አድራሻ እና ምናባዊ ቻናል ይመድባል። ለእያንዳንዱ ካሜራ ልዩ በሆነው I2C አድራሻ ልዩ የመሳሪያ ዛፍ ተደራቢ መፍጠር አለበት። የCSI-2 RX ሾፌር እያንዳንዱን ካሜራ ልዩ የሆነውን ምናባዊ ቻናል ቁጥር ይገነዘባል እና በእያንዳንዱ የካሜራ ዥረት የዲኤምኤ አውድ ይፈጥራል። ለእያንዳንዱ የዲኤምኤ አውድ የቪዲዮ መስቀለኛ መንገድ ተፈጥሯል። ከእያንዳንዱ ካሜራ የተገኘው መረጃ በዲኤምኤ በመጠቀም ወደ ማህደረ ትውስታው በትክክል ይቀመጣሉ እና ይከማቻሉ። የተጠቃሚ ቦታ መተግበሪያዎች የካሜራውን ውሂብ ለመድረስ ከእያንዳንዱ ካሜራ ጋር የሚዛመዱትን የቪዲዮ ኖዶች ይጠቀማሉ። ምሳሌamples of using this software architecture are given in Chapter 4 – Reference Design.
ከV4L2 ማዕቀፍ ጋር የሚስማማ ማንኛውም የተለየ ዳሳሽ ነጂ ይህን አርክቴክቸር ተሰክቶ መጫወት ይችላል። አዲስ ዳሳሽ ሾፌርን ወደ ሊኑክስ ኤስዲኬ እንዴት ማዋሃድ እንደሚቻል [8]ን ይመልከቱ።

Image Pipeline Software Architecture

The AM6x Linux SDK provides the GStreamer (GST) framework, which can be used in the ser space to integrate the image processing components for various applications. The Hardware Accelerators (HWA) on the SoC, such as the Vision Pre-processing Accelerator (VPAC) or ISP, video encoder/decoder, and deep learning compute engine, are accessed through GST plugins. VPAC (አይኤስፒ) ራሱ በርካታ ብሎኮች አሉት፣ እነዚህም ቪዥን ኢሜጂንግ ንዑስ ስርዓት (VISS)፣ የሌንስ መዛባት ማስተካከያ (ኤልዲሲ) እና መልቲስካላር (MSC) እያንዳንዳቸው ከጂኤስቲ ፕለጊን ጋር የሚዛመዱ።

Figure 3-2 shows the block diagram of a typical image pipeline from the camera to encoding or deep
learning applications on AM62A. For more details about the end-to-end data flow, refer to the EdgeAI SDK documentation.

For AM62P, the image pipeline is simpler because there is no ISP on AM62P.

ለእያንዳንዱ ካሜራ በተፈጠረ የቪዲዮ መስቀለኛ መንገድ፣ በGStreamer ላይ የተመሰረተ የምስል ቧንቧ መስመር በርካታ የካሜራ ግብአቶችን (በተመሳሳይ የ CSI-2 RX በይነገጽ የተገናኘ) በአንድ ጊዜ ማቀናበር ያስችላል። GStreamerን ለብዙ ካሜራ አፕሊኬሽኖች በመጠቀም የማመሳከሪያ ንድፍ በሚቀጥለው ምዕራፍ ተሰጥቷል።

የማጣቀሻ ንድፍ

ይህ ምዕራፍ የ Arducam V62Link Camera Solution Kit በመጠቀም 3 CSI-4 ካሜራዎችን ከ AM2A ጋር ለማገናኘት እና ለ62ቱም ካሜራዎች የነገር ማወቂያን በመጠቀም በ AM4A EVM ላይ ባለብዙ ካሜራ አፕሊኬሽኖችን የማሄድ የማመሳከሪያ ንድፍ ያቀርባል።

የሚደገፉ ካሜራዎች
The Arducam V3Link kit works with both FPD-Link/V3-Link-based cameras and Raspberry Pi-compatible CSI-2 cameras. The following cameras have been tested:

D3 Engineering D3RCM-IMX390-953
Leopard Imaging LI-OV2312-FPDLINKIII-110H

IMX219 cameras in the Arducam V3Link Camera Solution Kit

Setting up Four IMX219 Cameras
Follow the instructions provided in the AM62A Starter Kit EVM Quick Start Guide to set up the SK-AM62A-LP EVM (AM62A SK) and ArduCam V3Link Camera Solution Quick Start Guide to connect the cameras to AM62A SK through the V3Link kit. Make sure the pins on the flex cables, cameras, V3Link board, and AM62A SK are all aligned properly.

Figure 4-1 shows the setup used for the reference design in this report. The main components in the setup include:

1X SK-AM62A-LP EVM board
1X Arducam V3Link d-ch adapter board
FPC cable connecting Arducam V3Link to SK-AM62A

4X V3Link camera adapters (serializers)
4X RF coaxial cables to connect V3Link serializers to V3Link d-ch kit
4X IMX219 Cameras

4X CSI-2 22-pin cables to connect cameras to serializers
Cables: HDMI cable, USB-C to power SK-AM62A-LP and 12V power sourced for V3Link d-ch kit)
Other components not shown in Figure 4-1: micro-SD card, micro-USB cable to access SK-AM62A-LP, and Ethernet for streaming

Configuring Cameras and CSI-2 RX Interface
Set up the software according to the instructions provided in the Arducam V3Link Quick Start Guide. After running the camera setup script, setup-imx219.sh, the camera’s format, the CSI-2 RX interface format, and the routes from each camera to the corresponding video node will be configured properly. Four video nodes are created for the four IMX219 cameras. Command “v4l2-ctl –list-devices” displays all the V4L2 video devices, as shown below:

There are 6 video nodes and 1 media node under tiscsi2rx. Each video node corresponds to a DMA context allocated by the CSI2 RX driver. Out of the 6 video nodes, 4 are used for the 4 IMX219 cameras, as shown in the media pipe topology below:

ከላይ እንደሚታየው፣ የሚዲያ አካል 30102000.ticsi2rx 6 የምንጭ ፓድ አለው፣ ግን የመጀመሪያዎቹ 4 ብቻ ጥቅም ላይ ይውላሉ፣ እያንዳንዳቸው ለአንድ IMX219። የሚዲያ ፓይፕ ቶፖሎጂ እንዲሁ በግራፊክ ሊገለጽ ይችላል። ነጥብ ለመፍጠር የሚከተለውን ትዕዛዝ ያሂዱ file:

Then run the command below on a Linux host PC to generate a PNG file:

ምስል 4-2 ከላይ የተሰጡትን ትዕዛዞች በመጠቀም የተፈጠረ ምስል ነው. በስእል 3-1 የሶፍትዌር አርክቴክቸር ውስጥ ያሉት ክፍሎች በዚህ ግራፍ ውስጥ ይገኛሉ።

Streaming from Four Cameras
ሁለቱም ሃርድዌር እና ሶፍትዌሮች በትክክል ሲዋቀሩ፣ ባለብዙ ካሜራ መተግበሪያዎች ከተጠቃሚው ቦታ ሊሄዱ ይችላሉ። ለ AM62A፣ ጥሩ የምስል ጥራት ለማምረት አይኤስፒ መስተካከል አለበት። የአይኤስፒ ማስተካከያን እንዴት ማከናወን እንደሚቻል AM6xA ISP Tuning Guideን ይመልከቱ። የሚከተሉት ክፍሎች exampየካሜራ ውሂብን ወደ ማሳያ የማሰራጨት ፣ የካሜራ ውሂብን ወደ አውታረ መረብ የማሰራጨት እና የካሜራውን መረጃ ለማከማቸት files.

Streaming Camera Data to Display
የዚህ የባለብዙ ካሜራ ስርዓት መሰረታዊ አፕሊኬሽን ቪዲዮዎችን ከሁሉም ካሜራዎች ወደ ከተመሳሳይ ሶሲ ጋር ወደተገናኘ ማሳያ ማስተላለፍ ነው። የሚከተለው የ GStreamer ቧንቧ መስመር exampአራት IMX219ን ወደ ማሳያ የማሰራጨት (የቪዲዮ መስቀለኛ መንገድ ቁጥሮች እና በቧንቧ መስመር ውስጥ ያሉት v4l-subdev ቁጥሮች ከዳግም ማስነሳት ወደ ዳግም ማስነሳት ሊቀየሩ ይችላሉ።)

Streaming Camera Data through Ethernet
ከተመሳሳዩ ሶሲ ጋር ወደተገናኘ ማሳያ ከማሰራጨት ይልቅ የካሜራ ዳታ በኤተርኔት በኩል ሊሰራጭ ይችላል። የመቀበያው ጎን ሌላ AM62A/AM62P ፕሮሰሰር ወይም አስተናጋጅ ፒሲ ሊሆን ይችላል። የሚከተለው የቀድሞ ነውampየካሜራውን መረጃ በኤተርኔት በኩል የማሰራጨት (ለቀላልነት ሁለት ካሜራዎችን በመጠቀም) (በቧንቧው ውስጥ ጥቅም ላይ የዋለውን የመቀየሪያ ፕለጊን ልብ ይበሉ)

የሚከተለው የቀድሞ ነውampየካሜራውን መረጃ ለመቀበል እና በሌላ AM62A/AM62P ፕሮሰሰር ላይ ወደ ማሳያ መልቀቅ፡-

Storing Camera Data to Files
Instead of streaming to a display or through a network, the camera data can be stored in local fileኤስ. ከታች ያለው የቧንቧ መስመር የእያንዳንዱን ካሜራ ውሂብ ወደ ሀ file (ሁለት ካሜራዎችን እንደ የቀድሞample ለቀላልነት)።

Multicamera Deep Learning Inference

AM62A ጥልቅ የመማር ማፍጠኛ (C7x-MMA) የተገጠመለት እስከ ሁለት ቶፒኤስ ያለው ሲሆን ይህም የተለያዩ የጥልቅ መማሪያ ሞዴሎችን ለምድብ፣ ለዕቃ ፈልሳፊነት፣ ለትርጉም ክፍፍል እና ለሌሎችም ማስኬድ የሚችል ነው። ይህ ክፍል AM62A አራት ጥልቅ የመማሪያ ሞዴሎችን በአራት የተለያዩ የካሜራ ምግቦች ላይ እንዴት እንደሚያሄድ ያሳያል።

የሞዴል ምርጫ
The TI’s EdgeAI-ModelZoo provides hundreds of state-of-the-art models, which are converted/exported from their original training frameworks to an anembedded-friendlyy format so that they can be offloaded to the C7x-MMA deep learning accelerator. The cloud-based Edge AI Studio Model Analyzer provides an easy-to-use “Model Selection” tool. It is dynamically updated to include all models supported in TI EdgeAI-ModelZoo. The tool requires no previous experience and provides an easy-to-use interface to enter the features required in the desired model.

The TFL-OD-2000-ssd-mobV1-coco-mlperf was selected for this multi-camera deep learning experiment. This multi-object detection model is developed in the TensorFlow framework with a 300×300 input resolution. Table 4-1 shows the important features of this model when trained on the cCOCO dataset with about 80 different classes.

ሠንጠረዥ 4-1. የአምሳያው TFL-OD-2000-ssd-mobV1-coco-mlperf ባህሪያትን ያድምቁ።

ሞዴል	ተግባር	ጥራት	FPS	mAP 50% Accuracy On COCO	መዘግየት/ፍሬም (ሚሴ)	DDR BW Utilization (MB/ Frame)
TFL-OD-2000-ssd- mobV1-ኮኮ-mlperf	Multi Object Detection	300×300	~152	15.9	6.5	18.839

Pipeline Setup
Figure 4-3 shows the 4-camera deep learning GStreamer pipeline. TI provides a suite of GStreamer plugins አንዳንድ የሚዲያ ሂደትን እና ጥልቅ የመማሪያ መረጃን በሃርድዌር አፋጣኝ ላይ ለመጫን ያስችላል። አንዳንድ የቀድሞampከእነዚህ ውስጥ plugins tiovxisp፣ tiovxmultiscaler፣ tiovxmosaic እና tidlinferer ያካትታሉ። በስእል 4-3 ያለው የቧንቧ መስመር ሁሉንም አስፈላጊ ነገሮች ያካትታል plugins for a multipath GStreamer pipeline for 4-camera inputs, each with media preprocess, deep learning inference, and postprocess. The duplicated plugins ለቀላል ማሳያ ለእያንዳንዱ የካሜራ ዱካዎች በግራፉ ውስጥ ተከማችተዋል።
The available hardware resources are evenly distributed among the four camera paths. For instance, AM62A contains two image multiscalers: MSC0 and MSC1. The pipeline explicitly dedicates MSC0 to process camera 1 and camera 2 paths, while MSC1 is dedicated to camera 3 and camera 4.

The output of the four camera pipelines is scaled down and concatenated together using the tiovxmosaic plugin. The output is displayed on a single screen. Figure 4-4 shows the output of the four cameras with a deep learning model running object detection. Each pipeline (camera) is running at 30 FPS and a total of 120 FPS.

ቀጥሎ በስእል 4-3 ላይ ለሚታየው የመልቲ ካሜራ ጥልቅ ትምህርት አጠቃቀም ጉዳይ ሙሉ የቧንቧ መስመር ስክሪፕት ነው።

የአፈጻጸም ትንተና

The setup with four cameras using the V3Link board and the AM62A SK was tested in various application scenarios, including directly displaying on a screen, streaming over Ethernet (four UDP channels), recording to 4 separate files, and with deep learning inference. In each experiment, we monitored the frame rate and the utilization of CPU cores to explore the whole system’s capabilities.

ቀደም ሲል በስእል 4-4 እንደሚታየው የጥልቅ መማሪያ ቧንቧ መስመር የሲፒዩ ኮር ጭነቶችን በማያ ገጹ ግርጌ ላይ እንደ ባር ግራፍ ለማሳየት የ tiperfoverlay GStreamer ተሰኪን ይጠቀማል። በነባሪ፣ ሸክሞቹን እንደ የመጠቀሚያ መቶኛ ለማሳየት ግራፉ በየሁለት ሰከንድ ይዘምናል።tage. In addition to the tiperfoverlay GStreamer plugin, the perf_stats tool is a second option to show core performance directly on the terminal with an option for saving to a file. This tool is more accurate compared to the tTiperfoverlayas the latter adds extra load on theARMm cores and the DDR to draw the graph and overlay it on the screen. The perf_stats tool is mainly used to collect hardware utilization results in all of the test cases shown in this document. Some of the important processing cores and accelerators studied in these tests include the main processors (four A53 Arm cores @ 1.25GHz), the deep learning accelerator (C7x-MMA @ 850MHz), the VPAC (ISP) with VISS and multiscalers (MSC0 and MSC1), and DDR operations.

Table 5-1 shows the performance and resource utilization when using AM62A with four cameras for three use cases, including streaming four cameras to a display, streaming over Ethernet, and recording to four separate files. Two tests are implemented in each use case: with the camera only and with deep learning inference. In addition, the first row in Table 5-1 shows hardware utilizations when only the operating system was running on AM62A without any user applications. This is used as a baseline to compare against when evaluating hardware utilizations of the other test cases. As shown in the table, the four cameras with deep learning and screen display operated at 30 FPS each ,with a total of 120 FPS for the four cameras. This high frame rate is achieved with only 86% of the deep learning accelerator (C7x-MMA) full capacity. In addition, it is important to note that the deep learning accelerator was clocked at 850MHz instead of 1000MHz in these experiments, which is about only 85% of its maximum performance.

ሠንጠረዥ 5-1. ከ62 IMX4 ካሜራዎች ጋር ለስክሪን ማሳያ ሲጠቀሙ የ AM219A አፈጻጸም (FPS) እና የሀብት አጠቃቀም፣ የኤተርኔት ዥረት፣ ይቅዱ Fileዎች፣ እና ጥልቅ የመማሪያ ኢንፈረንሲንግ ማከናወን

መተግበሪያ n	Pipeline (operation )	ውፅዓት	FPS avg pipeline s	FPS ጠቅላላ	MPUs A53s @ 1.25 GHz [%]	MCU R5 [%]	DLA (C7x- MMA) @ 850 MHz [%]	VISS [%]	MSC0 [%]	MSC1 [%]	ዲ.ዲ.ዲ Rd [MB/s]	ዲ.ዲ.ዲ Wr [MB/s]	ዲ.ዲ.ዲ Total [MB/s]
መተግበሪያ የለም	Baseline No operation	NA	NA	NA	1.87	1	0	0	0	0	560	19	579
ካሜራ ብቻ	ዥረት to Screen	ስክሪን	30	120	12	12	0	70	61	60	1015	757	1782
	Stream over Ethernet	ዩዲፒ፡ 4 ports 1920×1080	30	120	23	6	0	70	0	0	2071	1390	3461
	መዝገብ ወደ files	4 files 1920×1080	30	120	25	3	0	70	0	0	2100	1403	3503
ካም with Deep learning	Deep learning: Object detection MobV1- coco	ስክሪን	30	120	38	25	86	71	85	82	2926	1676	4602
	Deep learning: Object detection MobV1- coco and Stream over Ethernet	ዩዲፒ፡ 4 ports 1920×1080	28	112	84	20	99	66	65	72	4157	2563	6720
	Deep learning: Object detection MobV1- coco and record to files	4 files 1920×1080	28	112	87	22	98	75	82	61	2024	2458	6482

ማጠቃለያ
This application report describes how to implement multi-camera applications on the AM6x family of devices. A reference design based on Arducam’s V3Link Camera Solution Kit and AM62A SK EVM is provided in the report, with several camera applications using four IMX219 cameras, such as streaming and object detection. Users are encouraged to acquire the V3Link Camera Solution Kit from Arducam and replicate these examples. The report also provides a detailed analysis of the performance of AM62A while using four cameras under various configurations, including displaying to a screen, streaming over Ethernet, and recording to files. It also showsAM62A’sA capability of performing deep learning inference on four separate camera streams in parallel. If there are any questions about running these examples፣ በTI E2E መድረክ ላይ ጥያቄ ያቅርቡ።

ዋቢዎች

AM62A Starter Kit EVM Quick Start Guide

ArduCam V3Link Camera Solution Quick Start Guide
Edge AI SDK documentation for AM62A
Edge AI Smart Cameras Using Energy-Efficient AM62A Processor

Camera Mirror Systems on AM62A
Driver and Occupancy Monitoring Systems on AM62A
Quad Channel Camera Application for Surround View and CMS Camera Systems

AM62Ax Linux Academy on Enabling CIS-2 Sensor
Edge AI ModelZoo
Edge AI Studio

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TI Parts Referred in This Application Note:

https://www.ti.com/product/AM62A7

ጠቃሚ ማሳሰቢያ እና የክህደት ቃል

ቲ ቴክኒካል እና አስተማማኝነት መረጃን (የመረጃ ወረቀቶችን ጨምሮ)፣ የንድፍ ምንጮች (የማጣቀሻ ንድፎችን ጨምሮ)፣ ማመልከቻ ወይም ሌላ የንድፍ ምክር፣ WEB መሳሪያዎች፣ የደህንነት መረጃ፣ እና ሌሎች ምንጮች “እንደሆነ” እና ከሁሉም ስህተቶች ጋር እና ሁሉንም ዋስትናዎች ፣የተገለፁ እና የተዘዋዋሪ ፣ያለ የሸቀጦች ዋስትናዎች ፣የባለስልጣናት ብቃትን ያለመቻልን ጨምሮ ሁሉንም ዋስትናዎች ውድቅ ያደርጋል። .

እነዚህ ግብዓቶች በቲአይ ምርቶች ዲዛይን ለሚሰሩ ገንቢዎች የታሰቡ ናቸው። እርስዎ ብቻ ተጠያቂ ነዎት

ለትግበራዎ ተገቢውን የቲአይ ምርቶችን መምረጥ ፣

መተግበሪያዎን መንደፍ፣ ማረጋገጥ እና መሞከር፣ እና
ensuring your application meets applicable standards, and any other safety, security, regulatory, or other requirements.

These resources are subject to change without notice. TI permits you to use these resources only for the development of an application that uses the TI products described in the resource. Other reproduction and display of these resources is prohibited. No license is granted to any other TI intellectual property right or to any third party intellectual property right. TI disclaims responsibility for, and you will fully indemnify TI and its representatives against, any claims, damages, costs, losses, and liabilities arising out of your use of these resources.

የቲአይ ምርቶች በቲአይ የሽያጭ ውል ወይም በ ላይ ባሉ ሌሎች የሚመለከታቸው ውሎች ተገዢ ናቸው። ቲ.ኮም ወይም ከእንደዚህ ዓይነት የቲአይ ምርቶች ጋር ተያይዞ የቀረበ። የቲ የነዚህን ግብአቶች አቅርቦት አይሰፋም ወይም በሌላ መልኩ አይቀይረውም የቲ የሚመለከተውን ዋስትና ወይም የዋስትና ማስተባበያ ለቲአይ ምርቶች።

TI እርስዎ ያቀረቡትን ማንኛውንም ተጨማሪ ወይም የተለየ ቃል ይቃወማል እና ውድቅ ያደርጋል።

ጠቃሚ ማሳሰቢያ

የፖስታ አድራሻ፡ ቴክሳስ መሣሪያዎች፣ ፖስታ ቤት ሣጥን 655303፣ ዳላስ፣ ቴክሳስ 75265

በተደጋጋሚ የሚጠየቁ ጥያቄዎች

ጥ፡ ማንኛውንም አይነት ካሜራ ከ AM6x ቤተሰብ መሳሪያዎች ጋር መጠቀም እችላለሁ?

The AM6x family supports different camera types, including those with or without built-in ISP. Refer to the specifications for more details on supported camera types.

: What are the main differences between AM62A and AM62P in image processing?

The key variations include supported camera types, camera output data, presence of ISP HWA, Deep Learning HWA, and 3-D Graphics HWA. Refer to the specifications section for a detailed comparison.

ሰነዶች / መርጃዎች

የቴክሳስ መሣሪያዎች AM6x በርካታ ካሜራን በማዳበር ላይ [pdf] የተጠቃሚ መመሪያ
AM62A፣ AM62P፣ AM6x ባለብዙ ካሜራ፣ AM6x፣ በርካታ ካሜራን በማዳበር ላይ፣ ባለብዙ ካሜራ፣ ካሜራ

ዋቢዎች

የተጠቃሚ መመሪያ

Texas Instruments AM6x Developing Multiple Cameras

ዝርዝሮች