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I need to build a Computer Vision and Deep Learning framework on NVIDIA Jetson TX2 Xavier devices

The project will be articulated in 3 phases, the first we will create the core, the part of the basic computer vision, which includes the configuration of the cameras, calibration, alignment and image optimization operations.

Then the Tracking, sensor fusion, identification and data reading functions

The last phase with we will implement the Machine and Deep Learning functionalities

Phase 1 dettail

Configuring LAN / USB video streams collection with json configuration file where details are listed (seonsore size, fov, type, etc.)

The camera can be RGB visual, thermal, stereoscopic

Create a function that calls answers with the cameras connected at same time

Distortion correction functions (calibration)

Video alignment features (different focal lengths and resolutions) in overlay with possible transparence

Video optimization for Track

Thermal spot evidence on R.G. B

Single element traking

Recognition of some object (like yolo)

Color recognition object

Vehicle and license plate recognition (plate color brand)

Traking rgb + thermal sensor fusion

Stereoscopic Deep Map from stereo cameras in overlay on the RGB

Integration with imu and gps and IMU

Geo tag position of tracked element (trigonometry)

The targhet of the framework are working on tx2 in a Unmanned vehicle UAV and on AUV Rover. In a first time the delopment and testing phase are executed on the ground. In a second moment, where the integration with the onboard sensors like GPS and IMU, for example, is complete all the tests will be done on a little UAV.

The final purpose of the framework will be very broad, being used for research and development in a university,

a part have targhet at the nature and safety and sorting of salvatic animals such as:

Identification of waste and plastic material for removal

Research, cataloging and sorting of wild animals for identification count and making safe (e.g. roe deer before haymaking)

Then a part for industrial waste in the energy sector:

Problem recognition and position reporting in photovoltaic systems

Cataloging of electric pylons and identification of problems such as overheating of joints or broken insulators

For these reasons there must be a reliable trigonometric algorithm of GeoTag

Compétences : OpenCV, Python, Programmation C++, Machine Learning (ML), Deep Learning

en voir plus : jetson agx xavier, jetson nano object detection, jetson nano, nvidia jetson tx2 projects, nvidia jetpack, jetson nano projects, nvidia jetson nano, jetson xavier

Concernant l'employeur :
( 0 commentaires ) Ancona, Italy

Nº du projet : #23394284

37 freelance font une offre moyenne de €1126 pour ce travail

iTinkerBell

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williams115

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