high_pass = gray - gaussed idx = 0 > high_pass high_pass[idx] = 0 # binarize the result idx = high_pass >= 0.05 high_pass[idx] = 1.0 idx = high_pass < 0.05 high_pass[idx] = 0.0 # use hough transform to detect straight lines__ raw lines from src.hough import hough_vertical_mask fn = result_dir + "hough_line" ptsv, linesv = hough_vertical_mask(high_pass, img, fn, save=False, show=False) # get lined image__ use brush to widen the lines from src.util import add_wide_lines canvas = Image.fromarray(np.zeros((height, width), dtype=np.uint8)) lined = add_wide_lines(linesv, canvas, height, width) # ========================= test_6 =================================== # find connected components and label them from scipy import ndimage labeled, num_obj = ndimage.label(lined == True) # set the highest and lowest point of each component as start and end point from src.util import saveline
high_pass = gray - gaussed idx = 0 > high_pass high_pass[idx] = 0 # binarize the result idx = high_pass >= 0.05 high_pass[idx] = 1.0 idx = high_pass < 0.05 high_pass[idx] = 0.0 # use hough transform to detect straight lines from src.hough import hough_vertical_mask fn = result_dir + "hough_line" ptsv, linesv = hough_vertical_mask(high_pass, fn, save=True) # get lined image from src.util import add_wide_lines canvas = Image.fromarray(np.zeros((height, width), dtype=np.uint8)) lined = add_wide_lines(linesv, canvas, height, width) fn = result_dir + "added_wide_lines" from src.util import saveimage_binary saveimage_binary(lined, fn, "added wide lines") # ========================= test_6 =================================== # find connected components and label them from scipy import ndimage
