- Link: https://www.pyimagesearch.com/2018/02/26/face-detection-with-opencv-and-deep-learning/
- Folder: 01_Deep_Learning_Face_Detection
In this section we'll learn how to apply face detection with OpenCV to single input images, videos, and webcams.
Commands used:
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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
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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
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Face detection with Webcam:
python detect_faces_video.py -p model/deploy.prototxt.txt -m model/res10_300x300_ssd_iter_140000.caffemodel
- Link: https://pyimagesearch.com/2018/07/19/opencv-tutorial-a-guide-to-learn-opencv/
- Folder: 02_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
- Link: https://pyimagesearch.com/2014/09/01/build-kick-ass-mobile-document-scanner-just-5-minutes/
- Folder: 03_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.