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PyImageSearch CrashCourse

Course

Day 1: Face detection with OpenCV and Deep Learning

In this section we'll learn how to apply face detection with OpenCV to single input images, videos, and webcams.

Commands used:

  • Face detection with Images:

    python detect_faces.py --image data/image.jpg --prototext model/deploy.prototxt.txt --model model/res10_300x300_ssd_iter_140000.caffemodel

    python detect_faces.py -i data/sample.jpg -p model/deploy.prototxt.txt -m model/res10_300x300_ssd_iter_140000.caffemodel

  • Face detection with Video:

    python detect_faces_video.py -v data/1.mp4 -p model/deploy.prototxt.txt -m model/res10_300x300_ssd_iter_140000.caffemodel

  • Face detection with Webcam:

    python detect_faces_video.py -p model/deploy.prototxt.txt -m model/res10_300x300_ssd_iter_140000.caffemodel

Day 2: OpenCV Tutorial

Tutorial 1: In this we are going to learn,

  • Loading and displaying an image
  • Accessing individual pixels
  • Array slicing and cropping
  • Resizing images
  • Rotating an image
  • Smoothing an image
  • Drawing on an image

Tutorial 2: Along the way we'll be:

  • Learning how to convert images to grayscale with OpenCV
  • Performing edge detection
  • Thresholding a grayscale image
  • Finding, counting, and drawing contours
  • Conducting erosion and dilation
  • Masking an image

Day 3: Document Scanner

Building a document scanner with OpenCV can be accomplished in just three simple steps:

Step 1 : Detect edges.

Step 2 : Use the edges in the image to find the contour(outline) representing the piece of paper being scanned.

Step 3 : Apply a perspective transform to obtain the top-down view of the document.

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