如何使用 Python OpenCV 拉伸线条以适合图像

Method #1: Just drawing the extended line (no coordinates)

->之前之后

这是一个函数，当给定点p1和p2时，将only draw延伸线.默认情况下，线条由图像边界剪裁.还有一个distance参数，用于确定从原始起点绘制多远，或直到直线到达图像的边界.如果需要新的(x1, y1)和(x2, y2)坐标，请参见第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()

Method #2: Full drawing with coordinates

如果你需要新的(x1, y1)和(x2, y2)坐标，它会变得更复杂一些，因为我们需要 for each 可能的情况计算得到的新点.可能的情况有水平、垂直、正倾斜、负倾斜和精确对角线.下面是两个新坐标点的结果:白色是原始线，绿色是延长线

竖的

(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)

左对角

(0, 0) (500, 500)

右对角

(0, 0) (500, 500)

密码

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))

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

# 水平的
# -------------------------------
# p1 = (100, 300)
# p2 = (400, 300)
# -------------------------------

# 正斜率
# -------------------------------
# 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)
# -------------------------------

# 负斜率
# -------------------------------
# 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()