import time, sensor, image from pyb import UART from image import SEARCH_EX, SEARCH_DS UART(3,115200,timeout_char=1000) # Reset sensor sensor.reset() # Set sensor settings sensor.set_contrast(1) sensor.set_gainceiling(16) # Max resolution for template matching with SEARCH_EX is QQVGA sensor.set_framesize(sensor.QQCIF) # You can set windowing to reduce the search image. #sensor.set_windowing(((640-80)//2, (480-60)//2, 80, 60)) sensor.set_pixformat(sensor.GRAYSCALE) # Load template. # Template should be a small (eg. 32x32 pixels) grayscale image. template = image.Image("/Right.pgm") template = image.Image("/Left.pgm") clock = time.clock() # Run template matching while (True): clock.tick() img = sensor.snapshot() # find_template(template, threshold, [roi, step, search]) # ROI: The region of interest tuple (x, y, w, h). # Step: The loop step used (y+=step, x+=step) use a bigger step to make it faster. # Search is either image.SEARCH_EX for exhaustive search or image.SEARCH_DS for diamond search # # Note1: ROI has to be smaller than the image and bigger than the template. # Note2: In diamond search, step and ROI are both ignored. r = img.find_template(template, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60)) l = img.find_template(template, 0.70, step=4, search=SEARCH_EX) if r: img.draw_rectangle(r,5) uart.read(RightTurn) if l: img.draw_rectangle(l,5) uart.read(LeftTurn) print(clock.fps())