Python OpenCV提取物体轮廓_python 轮廓提取

一、基础实验

#coding=gbk
import numpy as np
import matplotlib.pyplot as plt
import cv2


# 读入图像
img = cv2.imread('snake.png')

img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# 将颜色更改为RGB（从BGR）

plt.imshow(img_rgb)
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gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
#灰度图
ret, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
plt.imshow(binary, cmap='gray')
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contours, hierarchy = cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
contours_image = np.copy(img)
contours_image = cv2.drawContours(contours_image, contours, -1, (0,255,0), 3)
 #二进制阈值图像
plt.imshow(contours_image)
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练习: 找到每个轮廓的方向

def orientations(contours):
    angles = []
    for contour in contours:
        if len(contour) < 5:
            continue     
        # 拟合椭圆
        ellipse = cv2.fitEllipse(contour)
        # 提取角度
        angle = ellipse[2]
        angles.append(angle)

    return angles

# ---------------------------------------------------------- #
# 打印方向值
angles = orientations(contours)
print('Angles of each contour (in degrees): ' + str(angles))

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Angles of each contour (in degrees): [92.56619262695312, 0.0, 0.0, 96.2242660522461, 47.50788879394531, 1.298294186592102, 0.0029462939128279686]
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边界矩形

## TODO: 完成此功能，以便
## 它会返回原始图像的新裁剪版本
def left_hand_crop(image, selected_contour):
    """
    Left hand crop 
    :参数图像：原始图像
    :参数selectec_contour：将用于裁剪的轮廓
    :返回值: cropped_image, 左手周围的裁剪图像
    """
    
    ## TODO: 检测左手轮廓的边界矩形
    
    x, y, w, h = cv2.boundingRect(selected_contour)
    box_image = cv2.rectangle(contours_image, (x,y), (x+w,y+h), (200,0,200),2)
    
    ## TODO: 使用边界矩形的尺寸裁剪图像
    # 复制图像进行裁剪
    
    cropped_image = np.copy(box_image)
    cropped_image = box_image[y: y + h, x: x + w]
    
    return cropped_image


## TODO: 从列表中选择左侧轮廓
## 替换此值
selected_contour = contours[1]


# ---------------------------------------------------------- #
# 如果选择了轮廓
if(selected_contour is not None):
    # 调用带有该轮廓的裁剪函数作为参数
    cropped_image = left_hand_crop(img, selected_contour)
    plt.imshow(cropped_image)

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