本文通过示例代码展示了如何利用OpenCV进行形态学操作，包括闭合和开运算，来清理图像并拟合椭圆。针对需要在2像素精度内拟合椭圆的需求，通过调整图像尺寸和结构元素大小，提高处理速度。最后，通过findContours找到最外层轮廓并在原图上绘制。虽然没有预先了解圆的大小信息，但可以通过输入图像估计合适的形态学操作参数。
鉴于所示的示例图像，我对以下说法表示怀疑：which I've already used open/close morphology operations on (this is as clean as I can get it, trust me on this)
看了你的评论后For precision, I need it to be fit within about 2 pixels accuracy
我很确定，使用形态学运算可能有很好的近似值。在
请看以下代码：import cv2
# Load image (as BGR for later drawing the circle)
image = cv2.imread('images/hvFJF.jpg', cv2.IMREAD_COLOR)
# Convert to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Get rid of possible JPG artifacts (when do people learn to use PNG?...)
_, gray = cv2.threshold(gray, 128, 255, cv2.THRESH_BINARY)
# Downsize image (by factor 4) to speed up morphological operations
gray = cv2.resize(gray, dsize=(0, 0), fx=0.25, fy=0.25)
# Morphological Closing: Get rid of the hole
gray = cv2.morphologyEx(gray, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5)))
# Morphological opening:
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