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Haarcascades
 
 
images
images
 
 
Lecture 10.2 - Photo Denoising.ipynb
Lecture 10.2 - Photo Denoising.ipynb
 
 
Lecture 10.3 - Mini Project #12 - Photo Restoration using inpainting.ipynb
Lecture 10.3 - Mini Project #12 - Photo Restoration using inpainting.ipynb
 
 
Lecture 2.4 Getting Started with OpenCV.ipynb
Lecture 2.4 Getting Started with OpenCV.ipynb
 
 
Lecture 2.5 - Grayscaling.ipynb
Lecture 2.5 - Grayscaling.ipynb
 
 
Lecture 2.6 - Color Spaces.ipynb
Lecture 2.6 - Color Spaces.ipynb
 
 
Lecture 2.7 - Histograms.ipynb
Lecture 2.7 - Histograms.ipynb
 
 
Lecture 2.8 - Drawing Images.ipynb
Lecture 2.8 - Drawing Images.ipynb
 
 
Lecture 3.10 - Sharpening.ipynb
Lecture 3.10 - Sharpening.ipynb
 
 
Lecture 3.11 - Thresholding, Binarization and Adaptive Threholding.ipynb
Lecture 3.11 - Thresholding, Binarization and Adaptive Threholding.ipynb
 
 
Lecture 3.12 - Dilation, Erosion, Opening and Closing.ipynb
Lecture 3.12 - Dilation, Erosion, Opening and Closing.ipynb
 
 
Lecture 3.13 - Edge Detection and Image Gradients.ipynb
Lecture 3.13 - Edge Detection and Image Gradients.ipynb
 
 
Lecture 3.14 -Perspective and Affine Transforms.ipynb
Lecture 3.14 -Perspective and Affine Transforms.ipynb
 
 
Lecture 3.15 Mini Project #1 - Live Sketch Using Webcam.ipynb
Lecture 3.15 Mini Project #1 - Live Sketch Using Webcam.ipynb
 
 
Lecture 3.2 - Translations.ipynb
Lecture 3.2 - Translations.ipynb
 
 
Lecture 3.3 - Rotations.ipynb
Lecture 3.3 - Rotations.ipynb
 
 
Lecture 3.4 - Scaling, Resiizng and Interpolations.ipynb
Lecture 3.4 - Scaling, Resiizng and Interpolations.ipynb
 
 
Lecture 3.5 - Image Pyramids.ipynb
Lecture 3.5 - Image Pyramids.ipynb
 
 
Lecture 3.6 - Cropping.ipynb
Lecture 3.6 - Cropping.ipynb
 
 
Lecture 3.7 - Arithematic Operations.ipynb
Lecture 3.7 - Arithematic Operations.ipynb
 
 
Lecture 3.8 - Bitwise Operations and Masking.ipynb
Lecture 3.8 - Bitwise Operations and Masking.ipynb
 
 
Lecture 3.9 - Blurring.ipynb
Lecture 3.9 - Blurring.ipynb
 
 
Lecture 3.9 - Convolutions and Blurring.ipynb
Lecture 3.9 - Convolutions and Blurring.ipynb
 
 
Lecture 4.1 - Understanding Contours.ipynb
Lecture 4.1 - Understanding Contours.ipynb
 
 
Lecture 4.2 - Sorting Contours.ipynb
Lecture 4.2 - Sorting Contours.ipynb
 
 
Lecture 4.3 - Approximating Contours and Convex Hull.ipynb
Lecture 4.3 - Approximating Contours and Convex Hull.ipynb
 
 
Lecture 4.4 - Matching Contours by Shape.ipynb
Lecture 4.4 - Matching Contours by Shape.ipynb
 
 
Lecture 4.5 Mini Project #2 - Identifying Contours by Shape.ipynb
Lecture 4.5 Mini Project #2 - Identifying Contours by Shape.ipynb
 
 
Lecture 4.6 - Line Detection Using Hough Lines.ipynb
Lecture 4.6 - Line Detection Using Hough Lines.ipynb
 
 
Lecture 4.8 - Blob Detection.ipynb
Lecture 4.8 - Blob Detection.ipynb
 
 
Lecture 4.9 Mini Project #3 - Counting Circles and Ellipses.ipynb
Lecture 4.9 Mini Project #3 - Counting Circles and Ellipses.ipynb
 
 
Lecture 5.2 Mini Project #4 - Finding Waldo.ipynb
Lecture 5.2 Mini Project #4 - Finding Waldo.ipynb
 
 
Lecture 5.4 - Finding Corners.ipynb
Lecture 5.4 - Finding Corners.ipynb
 
 
Lecture 6.2 - Face and Eye Detection.ipynb
Lecture 6.2 - Face and Eye Detection.ipynb
 
 
Lecture 6.3 - Mini Project #6 - Car and Pedestrian Detection.ipynb
Lecture 6.3 - Mini Project #6 - Car and Pedestrian Detection.ipynb
 
 
Lecture 7.1 - Facial Landmarks.ipynb
Lecture 7.1 - Facial Landmarks.ipynb
 
 
Lecture 7.2 - Merging Faces.ipynb
Lecture 7.2 - Merging Faces.ipynb
 
 
Lecture 7.3 - Mini Project # 7 - Live Face Swaps.ipynb
Lecture 7.3 - Mini Project # 7 - Live Face Swaps.ipynb
 
 
Lecture 7.4 - Mini Project # 8 – Yawn Detector and Counting.ipynb
Lecture 7.4 - Mini Project # 8 – Yawn Detector and Counting.ipynb
 
 
Lecture 8.2 - Mini Project # 9 - Handwritten Digit Recognition.ipynb
Lecture 8.2 - Mini Project # 9 - Handwritten Digit Recognition.ipynb
 
 
Lecture 8.3 - Mini Project # 10 Face Recognition – Unlock Your Computer With Your Face!.ipynb
Lecture 8.3 - Mini Project # 10 Face Recognition – Unlock Your Computer With Your Face!.ipynb
 
 
Lecture 9.1 - Filtering by Color.ipynb
Lecture 9.1 - Filtering by Color.ipynb
 
 
Lecture 9.2 - Background Subtraction.ipynb
Lecture 9.2 - Background Subtraction.ipynb
 
 
Lecture 9.3 - Meanshift Object Tracking.ipynb
Lecture 9.3 - Meanshift Object Tracking.ipynb
 
 
Lecture 9.4 - Camshift Object Tracking.ipynb
Lecture 9.4 - Camshift Object Tracking.ipynb
 
 
Lecture 9.5 - Optical Flow Object Tracking.ipynb
Lecture 9.5 - Optical Flow Object Tracking.ipynb
 
 
Lecture 9.6 - Mini Project # 11 - Ball Tracking.ipynb
Lecture 9.6 - Mini Project # 11 - Ball Tracking.ipynb
 
 
README.md
README.md
 
 
output.jpg
output.jpg
 
 
output.png
output.png
 
 
output_shape_number_1.jpg
output_shape_number_1.jpg
 
 
output_shape_number_2.jpg
output_shape_number_2.jpg
 
 
output_shape_number_3.jpg
output_shape_number_3.jpg
 
 
output_shape_number_4.jpg
output_shape_number_4.jpg
 
 

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What I learnt from this course

  • Key concepts of computer Vision & OpenCV.
  • Perform image manipulations such as transformations, cropping, blurring, thresholding, edge detection and cropping.
  • Segment images by understanding contours, circle, and line detection. How to approximate contours, do contour filtering and ordering as well as approximations.
  • Feature detection (SIFT, SURF, FAST, BRIEF & ORB) for object detection.
  • Implement Object Detection for faces, people & cars.
  • Extract facial landmarks for face analysis, applying filters and face swaps.
  • Implement Machine Learning in Computer Vision for handwritten digit recognition.
  • Implement Facial Recognition.
  • Implement and understand Motion Analysis & Object Tracking.
  • Use basic computational photography techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old damaged photos).
  • Getting started in Deep Learning.

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