import cv2 as cv
import numpy as np

# 讀取圖像
img = cv.imread(args.image, cv.IMREAD_COLOR)

# HSV 閾值，獲取掩膜
def _threshold_hsv(image, lower, upper):
  hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
  mask = cv.inRange(hsv, lower, upper)
  result = cv.bitwise_and(image, image, mask=mask)
  return result, mask

_, thres = _threshold_hsv(img, np.array([0,110,190]), np.array([7,255,255]))

# 清除小點(diǎn)（可選）
kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3), (1, 1))
thres = cv.morphologyEx(thres, cv.MORPH_OPEN, kernel)

# 查找輪廓
#  cv.RETR_EXTERNAL: 只查找外部輪廓
contours, hierarchy = cv.findContours(
  threshold, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)

# 近似輪廓，減點(diǎn)（可選）
contours_poly = [cv.approxPolyDP(c, 3, True) for c in contours]

# 繪制輪廓
h, w = threshold.shape[:2]
drawing = np.zeros((h, w, 3), dtype=np.uint8)
for i in range(len(contours)):
  cv.drawContours(drawing, contours_poly, i, (0, 255, 0), 1, cv.LINE_8, hierarchy)

for contour in contours_poly:
  rect = cv.boundingRect(contour)
  cv.rectangle(drawing,
                (int(rect[0]), int(rect[1])),
                (int(rect[0]+rect[2]), int(rect[1]+rect[3])),
                (0, 255, 0), 2, cv.LINE_8)

for contour in contours_poly:
  center, radius = cv.minEnclosingCircle(contour)
  cv.circle(drawing, (int(center[0]), int(center[1])), int(radius),
            (0, 255, 0), 2, cv.LINE_8)