A repository containing all the work I have done so far with the Python OpenCV library. This is mostly following Programming Knowledge's YouTube tutorials. Thanks a lot!
- adaptive_thresh.py: applies binary thresholding and compares it to several types of adaptive thresholding on the same image
- binary.py: demonstrates bitwise and, or, not, and xor operations
- circle_detection.py: labels all circles in an image with a circle and a dot at the center
- drawing_on_imgs.py: draws various geometric shapes, including text, onto an image
- drawing_on_videos.py: displays the computer clock on webcam video
- edge_detection.py: displays several types of edge detection on the same image in matplotlib, including canny edge detection
- face_detection.py: detects human faces within an image and labels them with a box
- face_detection_vid.py: detects human faces in webcam video and labels them in real time with a box
- face_eye_detection.py: detects human faces and eyes in webcam video and labels them with a box
- find_contour.py: finds all contours within an image
- histograms.py: displays the intensity of all pixels in a grayscale image as a histogram using matplotlib
- histograms_color.py: displays the intensity of all pixels in an RGB/BGR image as three combined histograms using matplotlib
- hough_line.py: applies hough line transform theory using the HoughLines method (rough)
- hough_line_2.py: improved hough line detection using the HoughLinesP method
- image_blend.py: blends the left and right sides of two different images together
- image_view.py: displays a simple image with opencv in grayscale
- lane_detection.py: detects lanes within an image and displays them using matplotlib
- lane_detection_video.py detects lanes in real time within a video
- matplotlib_test.py: displays an image in matplotlib and normally
- messi.py: duplicates and moves a region of interest of an image and blends weighted images together
- morph.py: displays the same image with several morphological transformations applied in matplotlib
- motion_detection.py displays all movement within a video with a simple box. Works best when the video's camera is in a static position.
- mouseclick.py: displays an image and also displays the location (in x/y coords) where a mouseclick occurs
- mouseclick2.py: forms a line segment from any number of points in an image where a mouseclick occurs
- mouseclick3.py: displays the exact color of a pixel in a separate window when clicked on in an image
- obj_detection_video.py: continuously displays parts of the webcam feed based on whether they meet the HSV value thresholds specified by the user with the trackbar
- obj_tracking.py: displays parts of an image based on whether they meet the HSV value thresholds specified by the user with the trackbar
- pyramid.py: creates a basic image pyramid by increasing/decreasing the resolution of a single image.
- pyramid2.py: creates a laplacian pyramid from a single image.
- shape_detection.py detects simple shapes from a provided image.
- smoothing_blurring.py: performs several smoothing/blurring/filtering operations on a single image and displays using matplotlib
- template_matching.py: attempts to detect a smaller template image inside of a larger, separate image
- threshold.py: performs basic thresholding operations on the same image
- threshold2.py: performs basic thresholding operations on the same image and displays using matplotlib
- trackbar1.py: includes three trackbars that, when adjusted, results in an RGB color being displayed
- trackbar2.py: includes one trackbar representing an arbitrary value displayed on the image, and another trackbar setting color or grayscale for the image