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cv_tutorial

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Computer Vision Tutorial

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## Computer Vision Tutorial

_Computer Vision Tutorial_ includes classical theories and techniques and also recent ML/DL-based methods for computer vision. The tutorial covers classical theories and techniques such as image processing, camera projection models, camera calibration, and pose estimation. It also covers recent ML/DL-based methods including object categorization (and backbone networks) and its extensions such as object detection and instance segmentation. It also explains about further topics such as multi-object tracking, structure-from-motion, NeRF, and so on.

This tutorial has been initiated and maintained to teach undergraduate CSE students in [SEOULTECH](https://en.seoultech.ac.kr/) as the course of _Computer Vision_ (109079).

This tutorial contains concise code examples written in [Python](https://python.org/) with [OpenCV](https://opencv.org/) and [PyTorch](https://pytorch.org/).
* :bulb: Some code examples help readers understand how algorithms work internally.
* :wrench: Some code examples demonstrate how to use OpenCV functions in practical applications.
* :camera: Some code examples are from my 3D Vision Tutorial ([3dv_tutorial](https://github.com/mint-lab/3dv_tutorial)).

### Lecture Slides
* [Section 1. Introduction](https://github.com/mint-lab/cv_tutorial/blob/master/slides/01_introduction.pdf)
* [Section 2. Image Editing: Learning OpenCV](https://github.com/mint-lab/cv_tutorial/blob/master/slides/02_image_editing.pdf)
* [Section 3. Image Processing](https://github.com/mint-lab/cv_tutorial/blob/master/slides/03_image_processing.pdf)
* [Section 4. Color](https://github.com/mint-lab/cv_tutorial/blob/master/slides/04_color.pdf)
* [Section 5. Image Formation](https://github.com/mint-lab/cv_tutorial/blob/master/slides/05_image_formation.pdf)
* [Section 6. Image Geometry](https://github.com/mint-lab/cv_tutorial/blob/master/slides/06_image_geometry.pdf)
* [Section 7. Solving Problems](https://github.com/mint-lab/cv_tutorial/blob/master/slides/07_solving_problems.pdf)
* [Section 8. Image Correspondence](https://github.com/mint-lab/cv_tutorial/blob/master/slides/08_image_correspondence.pdf)
* [Section 9. Image Classification: CNN Backbones and Transfer Learning](https://github.com/mint-lab/cv_tutorial/blob/master/slides/09_image_classification.pdf)
* Section 10. Image Segmentation
* Section 11. Object Detection
* Section 12. Toward Vision Foundation Models
* Section 13. Object Tracking
* [Section 14. 3D Vision](https://github.com/mint-lab/cv_tutorial/blob/master/slides/14_3d_vision.pdf)

### Example Codes
* **Section 1. Introduction** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/01_introduction.pdf)
  * Note) How to install prerequisite packages in Python: `pip install -r requirements.txt`

* **Section 2. Image Editing: Learning OpenCV** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/02_image_editing.pdf)
  * OpenCV Image Representation
    * Image creation: [image_creation.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_creation.py) :bulb:
  * OpenCV Image and Video Input/Output
    * Image file viewer: [image_viewer.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_viewer.py) :wrench:
    * Image format converter: [image_converter.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_converter.py) :wrench:
    * Video file player: [video_player.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/video_player.py) :wrench:
    * Video format converter: [video_converter.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/video_converter.py) :wrench:
  * OpenCV Drawing Functions
    * Shape drawing: [shape_drawing.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/shape_drawing.py) :wrench:
  * OpenCV High-level GUI
    * (Handling keyboard events) Video file player with frame navigation: [video_player+navigation.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/video_player%2Bnavigation.py) :wrench:
    * (Handling mouse events) Free drawing: [free_drawing.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/free_drawing.py) :wrench:
  * Image Editing
    * Negative image and flip: [negative_image_and_flip.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/negative_image_and_flip.py) :bulb:
    * Intensity transformation with contrast and brightness: [intensity_transformation.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/intensity_transformation.py) :bulb:
    * (Image addition) Alpha blending: [alpha_blending.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/alpha_blending.py) :bulb:
    * (Image addition) Background extraction: [background_extraction.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/background_extraction.py) :bulb:
    * (Image subtraction) Image difference: [image_difference.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_difference.py) :bulb:
    * (Image subtraction) Background subtraction: [background_subtraction.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/background_subtraction.py) :bulb:
    * (Image crop) Image file viewer with the zoom window: [image_viewer+zoom.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_viewer%2Bzoom.py) :bulb:
    * Image resize with backward value copy: [image_resize.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_resize.py) :bulb:
    * Image rotation with backward/forward value copy: [image_rotation.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_rotation.py) :bulb:

* **Section 3. Image Processing** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/03_image_processing.pdf)
  * Intensity Transformation
    * Image histogram: [histogram.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/histogram.py) :bulb:
    * Contrast stretching with min-max stretching: [contrast_stretching.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/contrast_stretching.py) :bulb:
    * Histogram equalization: [histogram_equalization.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/histogram_equalization.py) :wrench:
    * Histogram equalization (from scratch): [histogram_equalization_implement.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/histogram_equalization_implement.py) :bulb:
  * Image Segmentation
    * Thresholding: [thresholding.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/thresholding.py) :wrench:
  * Image Filtering
    * Image filtering with various kernels: [image_filtering.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_filtering.py) :bulb:
    * Median filter: [median_filter.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/median_filter.py) :wrench:
    * Sobel edge detection: [Sobel_edge.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/Sobel_edge.py) :bulb:
    * Canny edge detection: [Canny_edge.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/Canny_edge.py) :wrench:
    * Bilateral filter: [bilateral_filter.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/bilateral_filter.py) :wrench:
  * Morphological Operations
    * Morphological operations with various operations and kernels: [morphology.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/morphology.py) :wrench:
    * Application) Background subtraction (foreground extraction): [background_subtraction.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/background_subtraction.py) :wrench:
  
* **Section 4. Color** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/04_color.pdf)
  * Color space conversion: [color_bgr2hsv.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/color_bgr2hsv.py) :wrench:
  * Color histogram equalization: [histogram_equalization+color.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/histogram_equalization+color.py) :bulb:

* **Section 5. Image Formation** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/05_image_formation.pdf)
  * Getting Started with 2D
    * 3D rotation conversion: [3d_rotation_conversion.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/3d_rotation_conversion.py) :camera:
  * Pinhole Camera Model
    * Object localization: [object_localization.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/object_localization.py) :camera:
    * Image formation: [image_formation.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/image_formation.py) :camera::bulb:
  * Geometric Distortion Models
    * Geometric distortion visualization: [distortion_visualization.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/distortion_visualization.py) :camera:
    * Geometric distortion correction: [distortion_correction.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/distortion_correction.py) :camera: [[result video]](https://youtu.be/HKetupWh4V8)
    * Geometric distortion correction with virtual PTZ [fisheye_virtual_ptz.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/fisheye_virtual_ptz.py) :camera:
  * Camera Calibration
    * Camera calibration: [camera_calibration.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/camera_calibration.py) :camera:
  * Absolute Camera Pose Estimation (a.k.a. perspective-n-point; PnP)
    * Pose estimation (chessboard): [pose_estimation_chessboard.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/pose_estimation_chessboard.py) :camera: [[result video]](https://youtu.be/4nA1OQGL-ig)
    * Pose estimation (book): [pose_estimation_book1.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/pose_estimation_book1.py) :camera:
    * Pose estimation (book) with camera calibration: [pose_estimation_book2.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/pose_estimation_book2.py) :camera:
    * Pose estimation (book) with camera calibration without initial $K$: [pose_estimation_book3.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/pose_estimation_book3.py) :camera: [[result video]](https://youtu.be/GYp4h0yyB3Y)

* **Section 6. Image Geometry** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/06_image_geometry.pdf)
  * Planar Homography
    * Perspective distortion correction: [perspective_correction.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/perspective_correction.py) :camera:
    * Planar image stitching: [image_stitching.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/image_stitching.py) :camera:
    * 2D video stabilization: [video_stabilization.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/video_stabilization.py) :camera: [[result video]](https://youtu.be/be_dzYicEzI)
  * Triangulation
    * Triangulation: [triangulation.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/triangulation.py) :camera:

* **Section 7. Solving Problems** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/07_solving_problems.pdf)
  * Solving Linear Equations in 3D Vision
    * Affine transformation estimation: [affine_estimation_implement](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/affine_estimation_implement.py) :camera: :bulb:
    * Planar homography estimation: [homography_estimation_implement](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/homography_estimation_implement.py) :camera: :bulb:
      * Appendix) Image warping using homography: [image_warping_implement.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/image_warping_implement.py) :camera: :bulb:
    * Triangulation: [triangulation_implement.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/triangulation_implement.py) :camera: :bulb:
  * Solving Nonlinear Equations in 3D Vision
    * Absolute camera pose estimation: [pose_estimation_implement.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/pose_estimation_implement.py) :camera: :bulb:
    * Camera calibration: [camera_calibration_implement.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/camera_calibration_implement.py) :camera: :bulb:
    * Camera calibration (with lens distortion): [camera_calibration_implement_k1.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/camera_calibration_implement_k1.py) :camera: :bulb:
  
* **Section 8. Image Correspondence** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/08_image_correspondence.pdf)
  * Feature Points and Descriptors
    * Harris corner (from scratch): [harris_corner_implement.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/harris_corner_implement.py) :camera: :bulb:
    * SuperPoint [[Github]](https://github.com/magicleap/SuperPointPretrainedNetwork)
  * Feature Matching and Tracking
    * Feature matching comparison: [feature_matching.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/feature_matching.py) :camera:
    * SuperGlue [[Github]](https://github.com/magicleap/SuperGluePretrainedNetwork)
    * Feature tracking with KLT tracker: [feature_tracking_klt.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/feature_tracking_klt.py) :camera:
  * Outlier Rejection
    * Line fitting with RANSAC: [line_fitting_ransac.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/line_fitting_ransac.py) :camera: :bulb:
    * Planar homography estimation with RANSAC: [image_stitching_implement.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/image_stitching_implement.py) :camera: :bulb:

* **Section 9. Image Classification: CNN Backbones and Transfer Learning** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/09_image_classification.pdf)
  * CNN Backbones
    * AlexNet implementation [[Github/PyTorch]](https://github.com/pytorch/vision/blob/main/torchvision/models/alexnet.py)
    * VGGNet implementation [[Github/PyTorch]](https://github.com/pytorch/vision/blob/main/torchvision/models/vgg.py)
    * GoogLeNet implementation [[Github/PyTorch]](https://github.com/pytorch/vision/blob/main/torchvision/models/googlenet.py)
    * ResNet implementation [[Github/PyTorch]](https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py)
  * Image classification with the pretrained ResNet-34 model: [image_classification.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_classification.py)

* **Section 10. Image Segmentation**
* **Section 11. Object Detection**
* **Section 12. Toward Vision Foundation Models**
* **Section 13. Object Tracking**
* **Section 14. 3D Vision** [[slides]](https://github.com/mint-lab/cv_tutorial/blob/master/slides/14_3d_vision.pdf)
  * Structure-from-Motion
    * COLMAP [[Homepage]](https://demuc.de/colmap/) [[Documentation]](https://colmap.github.io/) [[Github]](https://github.com/colmap/colmap)
  * 3D Representations
    * NeRF [[Homepage]](https://www.matthewtancik.com/nerf) [[Github]](https://github.com/bmild/nerf)

### Authors
* [Sunglok Choi](https://github.com/sunglok)

### Acknowledgements
The authors thank the following contributors and projects.

* Youngjin Hong: He reported two bugs in [image_rotation.py](https://github.com/mint-lab/cv_tutorial/blob/master/examples/image_rotation.py) and [object_localization.py](https://github.com/mint-lab/3dv_tutorial/blob/master/examples/object_localization.py).
* [ImageProcessingPlace.com](https://www.imageprocessingplace.com/root_files_V3/image_databases.htm) for test images (`lena.tif`, `baboon.tif`, and `peppers.tif`)
* [MOTChallenge](https://motchallenge.net/vis/PETS09-S2L1) for test images (`PETS09-S2L1-raw.webm`)
* [Wikipedia](https://en.wikipedia.org/wiki/Salt-and-pepper_noise) for a test image (`salt_and_pepper.png`)
* [OpenCV](https://github.com/opencv/opencv/tree/4.x/samples/data) for a test image (`sudoku.png`)

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