如何使用Python OpenCV拉伸一条线以适合图像？

Question

我有一个大小为 的图像W * H，我想在上面画一条线，并且该线应该自动适合图像，例如，如果我绘制它：

我要这个：

我如何在 Python 和 OpenCV 中做到这一点？谢谢

Answer 1

方法#1：仅绘制延长线（无坐标）

之前->之后

这是一个函数，当给定点p1和时p2，只会绘制延长线。默认情况下，该线被图像边界剪裁。还有一个distance参数用于确定从原始起点绘制多远或直到线到达图像的边界。如果您需要新的(x1, y1)和(x2, y2)坐标，请参阅第 #2 节

import cv2
import numpy as np

"""
@param: p1 - starting point (x, y)
@param: p2 - ending point (x, y)
@param: distance - distance to extend each side of the line
"""
def extend_line(p1, p2, distance=10000):
    diff = np.arctan2(p1[1] - p2[1], p1[0] - p2[0])
    p3_x = int(p1[0] + distance*np.cos(diff))
    p3_y = int(p1[1] + distance*np.sin(diff))
    p4_x = int(p1[0] - distance*np.cos(diff))
    p4_y = int(p1[1] - distance*np.sin(diff))
    return ((p3_x, p3_y), (p4_x, p4_y))

# Create blank black image using Numpy
original = np.zeros((500,500,3), dtype=np.uint8)
image1 = original.copy()
p1 = (250, 100)
p2 = (375, 250)
cv2.line(image1, p1, p2, [255,255,255], 2)

# Second image, calculate new extended points
image2 = original.copy()
p3, p4 = extend_line(p1, p2)
cv2.line(image2, p3, p4, [255,255,255], 2)

cv2.imshow('image1', image1)
cv2.imshow('image2', image2)
cv2.waitKey()

方法#2：用坐标完整绘图

如果您需要新的(x1, y1)和(x2, y2)坐标，它会变得有点复杂，因为我们需要为每种可能的情况计算结果新点。可能的情况是水平、垂直、正斜率、负斜率和精确对角线。这是具有新两个坐标点的每种情况的结果：白色是原始线，绿色是延长线

垂直的

(250, 0) (250, 500)

水平的

(0, 300) (500, 300)

正斜率

(0, 450) (450, 0)

负斜率

(0, 142) (500, 428)

左角对角线

(0, 0) (500, 500)

右角对角线

(0, 0) (500, 500)

代码

import numpy as np
import cv2
import math

"""
@param: dimensions - image shape from Numpy (h, w, c)
@param: p1 - starting point (x1, y1)
@param: p2 - ending point (x2, y2)
@param: SCALE - default parameter to ensure that extended lines go through borders
"""
def extend_line(dimensions, p1, p2, SCALE=10):
    # Calculate the intersection point given (x1, y1) and (x2, y2)
    def line_intersection(line1, line2):
        x_diff = (line1[0][0] - line1[1][0], line2[0][0] - line2[1][0])
        y_diff = (line1[0][1] - line1[1][1], line2[0][1] - line2[1][1])

        def detect(a, b):
            return a[0] * b[1] - a[1] * b[0]

        div = detect(x_diff, y_diff)
        if div == 0:
           raise Exception('lines do not intersect')

        dist = (detect(*line1), detect(*line2))
        x = detect(dist, x_diff) / div
        y = detect(dist, y_diff) / div
        return int(x), int(y)

    x1, x2 = 0, 0
    y1, y2 = 0, 0
    
    # Extract w and h regardless of grayscale or BGR image
    if len(dimensions) == 3:
        h, w, _ = dimensions
    elif len(dimensions) == 2:
        h, w = dimensions
    
    # Take longest dimension and use it as maxed out distance
    if w > h:
        distance = SCALE * w
    else:
        distance = SCALE * h
    
    # Reorder smaller X or Y to be the first point
    # and larger X or Y to be the second point
    try:
        slope = (p2[1] - p1[1]) / (p1[0] - p2[0])
        # HORIZONTAL or DIAGONAL
        if p1[0] <= p2[0]:
            x1, y1 = p1
            x2, y2 = p2
        else:
            x1, y1 = p2
            x2, y2 = p1
    except ZeroDivisionError:
        # VERTICAL
        if p1[1] <= p2[1]:
            x1, y1 = p1
            x2, y2 = p2
        else:
            x1, y1 = p2
            x2, y2 = p1
    
    # Extend after end-point A
    length_A = math.sqrt((x2 - x1)**2 + (y2 - y1)**2)
    p3_x = int(x1 + (x1 - x2) / length_A * distance)
    p3_y = int(y1 + (y1 - y2) / length_A * distance)

    # Extend after end-point B
    length_B = math.sqrt((x1 - x2)**2 + (y1 - y2)**2)
    p4_x = int(x2 + (x2 - x1) / length_B * distance)
    p4_y = int(y2 + (y2 - y1) / length_B * distance)
   
    # -------------------------------------- 
    # Limit coordinates to borders of image
    # -------------------------------------- 
    # HORIZONTAL
    if y1 == y2:
        if p3_x < 0: 
            p3_x = 0
        if p4_x > w: 
            p4_x = w
        return ((p3_x, p3_y), (p4_x, p4_y))
    # VERTICAL
    elif x1 == x2:
        if p3_y < 0: 
            p3_y = 0
        if p4_y > h: 
            p4_y = h
        return ((p3_x, p3_y), (p4_x, p4_y))
    # DIAGONAL
    else:
        A = (p3_x, p3_y)
        B = (p4_x, p4_y)

        C = (0, 0)  # C-------D
        D = (w, 0)  # |-------|
        E = (w, h)  # |-------|
        F = (0, h)  # F-------E
        
        if slope > 0:
            # 1st point, try C-F side first, if OTB then F-E
            new_x1, new_y1 = line_intersection((A, B), (C, F))
            if new_x1 > w or new_y1 > h:
                new_x1, new_y1 = line_intersection((A, B), (F, E))

            # 2nd point, try C-D side first, if OTB then D-E
            new_x2, new_y2 = line_intersection((A, B), (C, D))
            if new_x2 > w or new_y2 > h:
                new_x2, new_y2 = line_intersection((A, B), (D, E))

            return ((new_x1, new_y1), (new_x2, new_y2))
        elif slope < 0:
            # 1st point, try C-F side first, if OTB then C-D
            new_x1, new_y1 = line_intersection((A, B), (C, F))
            if new_x1 < 0 or new_y1 < 0:
                new_x1, new_y1 = line_intersection((A, B), (C, D))
            # 2nd point, try F-E side first, if OTB then E-D
            new_x2, new_y2 = line_intersection((A, B), (F, E))
            if new_x2 > w or new_y2 > h:
                new_x2, new_y2 = line_intersection((A, B), (E, D))
            return ((new_x1, new_y1), (new_x2, new_y2))

# Vertical
# -------------------------------
# p1 = (250, 100)
# p2 = (250, 300)
# -------------------------------

# Horizontal
# -------------------------------
# p1 = (100, 300)
# p2 = (400, 300)
# -------------------------------

# Positive slope
# -------------------------------
# C-F, C-D
# p1 = (50, 400)
# p2 = (400, 50)

# C-F, E-D
# p1 = (50, 400)
# p2 = (400, 50)

# F-E, E-D
# p2 = (250, 400)
# p1 = (400, 250)

# F-E, C-D
# p2 = (250, 400)
# p1 = (300, 250)
# -------------------------------

# Negative slope
# -------------------------------
# C-F, E-D
# p1 = (100, 200)
# p2 = (450, 400)

# C-F, F-E
# p2 = (100, 200)
# p1 = (250, 400)

# C-D, D-E
# p1 = (100, 50)
# p2 = (450, 400)

# C-D, F-E
p1 = (100, 50)
p2 = (250, 400)
# -------------------------------

# Exact corner diagonals
# -------------------------------
# p1 = (50,50)
# p2 = (300, 300)

# p2 = (375, 125)
# p1 = (125, 375)
# -------------------------------

image = np.zeros((500,500,3), dtype=np.uint8)
p3, p4 = extend_line(image.shape, p1, p2)
print(p3, p4)
cv2.line(image, p3, p4, [255,255,255], 2)
cv2.line(image, p1, p3, [36,255,12], 2)
cv2.line(image, p2, p4, [36,255,12], 2)
cv2.imshow('image', image)
cv2.waitKey()