# python图像处理代码块

这里一一列出工作中总结一些简单代码块
关于图像处理的
比如旋转缩放等等。。。。

# 图片等比例旋转

# 以点img中心为中心，旋转angle度，兼容mask
def rotateImg(img, angle, rotPoint=None):
    height,width = img.shape[:2]
    if rotPoint is None:
        rotPoint = width //2, height//2
    M = cv2.getRotationMatrix2D(rotPoint, -angle,1.0)
    dimension = (width,height)
    # print(img.shape)
    return cv2.warpAffine(img, M, dimension)

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# 旋转一个坐标点

# 以点img中心为中心，旋转angle度，兼容mask
def rotateImg(img, angle, rotPoint=None):
    height,width = img.shape[:2]
    if rotPoint is None:
        rotPoint = width //2, height//2
    M = cv2.getRotationMatrix2D(rotPoint, -angle,1.0)
    dimension = (width,height)
    # print(img.shape)
    return cv2.warpAffine(img, M, dimension)

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# 图片转base64

def image_to_base64(image_np):
    image = cv2.imencode('.png', image_np)[1]
    image_code = str(base64.b64encode(image))[2:-1]
    return image_code

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# 在图片上画圆、矩形、点

画矩形

leftTop = (0,0) # 必须为元组
rightBottom = (12,12) # 必须为元组
color = (255,255,255) # 必须为元组
thiness = -1 # 整数，-1代表实心填充
cv2.rectangle(img, leftTop, rightBottom, color, thiness)

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画圆

cv2.circle(img, center, radius, color[, thickness[, lineType[, shift]]])

画点(当参数 chinkness = -1 是就是点了)

cv2.circle(img, center, radius, color[, thickness[, lineType[, shift]]])

# 图片二值化求轮廓

求轮廓的详细信息、层级等 (opens new window)

_, mask = cv2.threshold(mask, 100, 255, cv2.THRESH_BINARY)
cs, hs = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

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# opencv-python 中文路径图片读取和保存

如果图片的存储路径存在中文
保险起见建议使用一下方法代替 cv2.imread() cv2.imwrite()

def imread(im_name):
    return cv2.imdecode(np.fromfile(im_name,dtype=np.uint8),-1)

def imwrite(savePath, img):
    cv2.imencode(f'{Path(savePath).suffix}', img)[1].tofile(savePath)

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# 求mask的最大内接圆

先求mask的轮廓（注意使用求轮廓方法获取的是轮廓的列表）
这里求一张图片里面最大轮廓

contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
areas = ([cv2.contourArea(contour) for contour in contours])
maxId = np.argmax(areas) 
maxCountour = contours[maxId]  # 最大轮廓

# 开始求这个轮廓的最大内接圆
# 最大内接圆和最小外切圆计算宽高
raw_dist = np.empty(mask.shape, dtype=np.float32)
for i in range(mask.shape[0]):
    for j in range(mask.shape[1]):
        raw_dist[i,j] = cv2.pointPolygonTest(maxCountour, (j,i), True)
_, maxVal, _, _ = cv2.minMaxLoc(raw_dist)

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