A repository where we can gather our tools for pattern recognition in the 2S Module Assembly. In images there is a number of pictures of dummy and glass sensors.
We can start by tuning the algorithms to smoothly detect these edges. The edge_finder.py contains a function called edge_find that uses the Canny algorithm to do edge detection. It then has two methods for extracting the edge coordinates. One method relies on finding contours with OpenCV, the other fits a line using a hough transform.
still_images.py runs this functions on still images, which we can use to optimize the algorithm on the sensor images.
real_time.py runs on a video feed, or on a video file.
comb_measure.py runs the sensor measurements and moves the stages accordingly. Two measurement types exist: measuring all sensor edges, and distance measurement of top and bottom corner.
focusing_algo.py is used to autofocus during a measurement.
image_processing.py prepares the images for edge and corner detection.
check_sharpness.py analyzes the sharpness of the sensor images and is required to run the z focusing in the actual measurement.
check_corners.py checks if all four corners of the sensor are properly within the image frame.
helpers.py contains small functions, e.g. for measuring the distance between lines, finding line intersections etc.
Python, OpenCV and NumPy