import cv2 import math def image_resize(image, width = None, height = None, inter = cv2.INTER_AREA): dim = None (h, w) = image.shape[:2] if width is None and height is None: return image if width is None: r = height / float(h) dim = (int(w * r), height) else: r = width / float(w) dim = (width, int(h * r)) resized = cv2.resize(image, dim, interpolation = inter) return resized def display (image) : resized = image_resize(image, 800, 800) cv2.imshow('img', resized) while cv2.getWindowProperty('img', cv2.WND_PROP_VISIBLE) > 0: key = cv2.waitKey(0) if key == 27: cv2.destroyAllWindows() break exit(0) # taken from # https://gist.github.com/phn/1111712/35e8883de01916f64f7f97da9434622000ac0390 def normalize_angle (num, lower=0.0, upper=360.0, b=False): """Normalize number to range [lower, upper) or [lower, upper]. Parameters ---------- num : float The number to be normalized. lower : float Lower limit of range. Default is 0.0. upper : float Upper limit of range. Default is 360.0. b : bool Type of normalization. See notes. Returns ------- n : float A number in the range [lower, upper) or [lower, upper]. Raises ------ ValueError If lower >= upper. Notes ----- If the keyword `b == False`, the default, then the normalization is done in the following way. Consider the numbers to be arranged in a circle, with the lower and upper marks sitting on top of each other. Moving past one limit, takes the number into the beginning of the other end. For example, if range is [0 - 360), then 361 becomes 1. Negative numbers move from higher to lower numbers. So, -1 normalized to [0 - 360) becomes 359. If the keyword `b == True` then the given number is considered to "bounce" between the two limits. So, -91 normalized to [-90, 90], becomes -89, instead of 89. In this case the range is [lower, upper]. This code is based on the function `fmt_delta` of `TPM`. Range must be symmetric about 0 or lower == 0. Examples -------- >>> normalize(-270,-180,180) 90 >>> import math >>> math.degrees(normalize(-2*math.pi,-math.pi,math.pi)) 0.0 >>> normalize(181,-180,180) -179 >>> normalize(-180,0,360) 180 >>> normalize(36,0,24) 12 >>> normalize(368.5,-180,180) 8.5 >>> normalize(-100, -90, 90, b=True) -80.0 >>> normalize(100, -90, 90, b=True) 80.0 >>> normalize(181, -90, 90, b=True) -1.0 >>> normalize(270, -90, 90, b=True) -90.0 """ # abs(num + upper) and abs(num - lower) are needed, instead of # abs(num), since the lower and upper limits need not be 0. We need # to add half size of the range, so that the final result is lower + # or upper - , respectively. res = num if not b: if lower >= upper: raise ValueError("Invalid lower and upper limits: (%s, %s)" % (lower, upper)) res = num if num > upper or num == lower: num = lower + abs(num + upper) % (abs(lower) + abs(upper)) if num < lower or num == upper: num = upper - abs(num - lower) % (abs(lower) + abs(upper)) res = lower if res == upper else num else: total_length = abs(lower) + abs(upper) if num < -total_length: num += math.ceil(num / (-2 * total_length)) * 2 * total_length if num > total_length: num -= math.floor(num / (2 * total_length)) * 2 * total_length if num > upper: num = total_length - num if num < lower: num = -total_length - num res = num * 1.0 # Make all numbers float, to be consistent return res