如何在Python版OpenCV 3中创建Rect对象？解决引用找不到问题

Hey there! Let's break down the issue you're facing and fix it up.

First, the core problem: Python's OpenCV bindings don't have a cv2.Rect class—this is a key difference from C++ OpenCV, where cv::Rect is a built-in class. That's exactly why you're seeing that "Cannot find reference" error when trying to call cv2.Rect(p1, p2).

Since you want to create a rectangle object to use methods like area(), here are a few straightforward solutions:

1. Use basic tuple operations (quickest approach) #

In Python OpenCV, rectangles are typically represented as a tuple (x, y, width, height). You can easily implement the functionality you need with simple functions:

# Define your rectangle using two diagonal points
p1 = (10, 20)
p2 = (40, 60)

# Convert points to the standard (x, y, w, h) tuple
x = min(p1[0], p2[0])
y = min(p1[1], p2[1])
w = abs(p1[0] - p2[0])
h = abs(p1[1] - p2[1])
rect = (x, y, w, h)

# Calculate area
def rect_area(rect):
    return rect[2] * rect[3]

print(rect_area(rect))  # Output: 1200

2. Create a custom Rect class (object-oriented approach) #

If you prefer a more class-based interface (similar to C++'s cv::Rect), you can build your own simple class with the methods you need:

class Rect:
    def __init__(self, p1, p2):
        # Initialize from two diagonal points
        self.x = min(p1[0], p2[0])
        self.y = min(p1[1], p2[1])
        self.width = abs(p1[0] - p2[0])
        self.height = abs(p1[1] - p2[1])
    
    def area(self):
        return self.width * self.height
    
    def contains(self, point):
        # Check if a (x, y) point is inside the rectangle
        px, py = point
        return self.x <= px <= self.x + self.width and self.y <= py <= self.y + self.height

# Usage example
my_rect = Rect((5, 5), (35, 45))
print(my_rect.area())  # Output: 1200
print(my_rect.contains((15, 25)))  # Output: True

3. Work with OpenCV's built-in rectangle outputs #

If you're getting rectangles from other OpenCV functions (like cv2.boundingRect() which returns a (x, y, w, h) tuple), you can either use it directly or pass its values to your custom Rect class:

# Example: Get bounding rectangle from a contour
contour = ...  # From cv2.findContours()
bounding_rect = cv2.boundingRect(contour)

# Convert to custom Rect class
my_rect = Rect((bounding_rect[0], bounding_rect[1]), 
               (bounding_rect[0]+bounding_rect[2], bounding_rect[1]+bounding_rect[3]))

To sum up: Python OpenCV favors lightweight data structures over complex classes, so you'll need to either use tuples with helper functions or roll your own class to replicate cv::Rect behavior.

内容的提问来源于stack exchange，提问作者Amit Keinan