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Materials for the course "Computer Vision in Autonomous Driving Tasks"

Content [in development]

  • Module 1 Basic image operation - Reading, writing and displaying images - Grayscaling - Cropping - Drawing images and shapes using OpenCV - Scaling, re-sizing and interpolations - Arithmetic Operations - Bitwise Operations and Masking
  • Module 1a Camera, project and reproject points, bev transform - Translations - Rotations
  • Module 1b Camera calibration - Calibration - Fish eye calibration - Desk pose visualization - Camera pose estimation
  • Module 1c Image compression
  • Module 2 Image preprocessing - Filters - Histogram - ColorSpaces
  • Module 2a Morphology
  • Module 3 Edge detector - Haris corner detector - Shi Tomasi corner detector
  • Module 4a Feature point detector - SIFT - ORB - FAST - descriptor extract - HOG
  • Module 4b Feature tracking, image comparison, Network detectors - RANSAC - NN - SuperPoint - SuperGlue
  • Module 5 Hough Detector for camera calibration - Line Extract - Camera Pose estimation by line
  • Module 5c Area detector. Segmentattion mapping - Graph base segmentation
  • Module 6 Optical flow - Dense and sparse optical flow - Video stabilization - Moving object detect - Slow Mo
  • Module 7 Stereovision. Disparity map, 3d point create
  • Module 7a Stereovision. Camera calibration
  • Module 8 Visual odometry
  • Module 9 Structure for motion
  • Module 10 Video and inertial data fusion
  • Module 11 Lidar data processing

Data

link for data https://cloud.mail.ru/public/abmx/Li8kWSVrU

Requirements

python 3.9 opencv 3.4.9

Installation

With Makefile

make fullinstall

Or manually

pip install .
wget "https://cloclo.datacloudmail.ru/zip64/V7eVPRE2ArgWYvm1S3EPI4ckr8WGSwFKbAW0u9Nk2Mb5YRcNtM79HweQNY/data.zip"
unzip data.zip
rm -rf data.zip

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app examples for the cv course

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