【python】库丨opencv-python丨

​

1、普通安装。

# 进入环境
pip install opencv-python

2、扩展安装。（针对cv2中缺少部分函数）

module’ object has no attribute ‘xfeatures2d’ (已解决）_小白狐狸的博客-CSDN博客_xfeatures2d

# 如果已经安装OpenCv2，则需要先卸载pip uninstall opencv-python再安装
pip install opencv-contrib-python

包下载地址：opencv-contrib-python · PyPI

import cv2
import numpy as np

image1 = cv2.imread('图片地址')
image1.astype(np.int32)
image2 = cv2.imread('图片地址')
image2.astype(np.int32)

visual_image = []

image1 = np.lib.pad(image1, ((0, 0), (0, 64), (0, 0)),  # ((上方, 下方),(左边,右边),(通道上,通道下) )
'constant',constant_values=0)
visual_image.append(image1)
visual_image.append(image2)
rank_image = np.concatenate(visual_image,1)
cv2.imshow('image', rank_image)
cv2.waitKey(0)

结果：

使用 cv2.warpAffine() 函数。参考代码：Self-Correction-Human-Parsing.

import numpy as np
import cv2

def PadResize(img_path='', reshape_size=[512,512]):
    aspect_ratio = reshape_size[1] * 1.0 / reshape_size[0]
    reshape_size = np.asarray(reshape_size)

    def _box2cs(box):
        x, y, w, h = box[:4]
        return _xywh2cs(x, y, w, h)

    def _xywh2cs(x, y, w, h):
        center = np.zeros((2), dtype=np.float32)
        center[0] = x + w * 0.5
        center[1] = y + h * 0.5
        if w > aspect_ratio * h:
            h = w * 1.0 / aspect_ratio
        elif w < aspect_ratio * h:
            w = h * aspect_ratio
        scale = np.array([w, h], dtype=np.float32)
        return center, scale

    def get_3rd_point(a, b):
        direct = a - b
        return b + np.array([-direct[1], direct[0]], dtype=np.float32)

    def get_dir(src_point, rot_rad):
        sn, cs = np.sin(rot_rad), np.cos(rot_rad)

        src_result = [0, 0]
        src_result[0] = src_point[0] * cs - src_point[1] * sn
        src_result[1] = src_point[0] * sn + src_point[1] * cs

        return src_result

    def get_affine_transform(center,
                             scale,
                             rot,
                             output_size,
                             shift=np.array([0, 0], dtype=np.float32),
                             inv=0):
        if not isinstance(scale, np.ndarray) and not isinstance(scale, list):
            print(scale)
            scale = np.array([scale, scale])

        scale_tmp = scale

        src_w = scale_tmp[0]
        dst_w = output_size[1]
        dst_h = output_size[0]

        rot_rad = np.pi * rot / 180
        src_dir = get_dir([0, src_w * -0.5], rot_rad)
        dst_dir = np.array([0, (dst_w - 1) * -0.5], np.float32)

        src = np.zeros((3, 2), dtype=np.float32)
        dst = np.zeros((3, 2), dtype=np.float32)
        src[0, :] = center + scale_tmp * shift
        src[1, :] = center + src_dir + scale_tmp * shift
        dst[0, :] = [(dst_w - 1) * 0.5, (dst_h - 1) * 0.5]
        dst[1, :] = np.array([(dst_w - 1) * 0.5, (dst_h - 1) * 0.5]) + dst_dir

        src[2:, :] = get_3rd_point(src[0, :], src[1, :])
        dst[2:, :] = get_3rd_point(dst[0, :], dst[1, :])

        if inv:
            trans = cv2.getAffineTransform(np.float32(dst), np.float32(src))
        else:
            trans = cv2.getAffineTransform(np.float32(src), np.float32(dst))

        return trans

    ### 1. Read and Visualize Img ###
    img = cv2.imread(img_path, cv2.IMREAD_COLOR)
    h, w, _ = img.shape
    cv2.imshow('ORI', img)

    ### 2. Get person center and scale ###
    person_center, s = _box2cs([0, 0, w - 1, h - 1])
    r = 0
    trans = get_affine_transform(person_center, s, r, reshape_size)

    ### 3. Resizing by adopting Padding.  ###
    reshaped_img = cv2.warpAffine(
        img,
        trans,
        (int(reshape_size[1]), int(reshape_size[0])),
        flags=cv2.INTER_LINEAR,
        borderMode=cv2.BORDER_CONSTANT,
        borderValue=(255, 150, 100))

    return reshaped_img

reshaped_img = PadResize( img_path='./demo/demo.jpg',
                          reshape_size=[512,512] )
cv2.imshow('RESHAPE', reshaped_img)
cv2.imwrite('demo_resized.png', reshaped_img)
cv2.waitKey(0)

输入图片： ./demo/demo.jpg

输出图片： ./demo_resized.png

↑蓝色就是填充的部分。

​

1、dst = cv2.divide(m1, m2)函数，当除数m2中有“0”时，dst返回值为0而不是inf。

import cv2
import numpy as np

gradx = np.array([0,0,3])
grady = np.array([1,2,3])
dst1 = cv2.divide(gradx, grady)
dst2 = cv2.divide(grady, gradx)
print(dst1, 'n')
print(dst2, 'n')

【实验结果】
[[0]
 [0]
 [1]] 

[[0]
 [0]
 [1]] 

​​
​

1、cv2.cv.Boxpoint() 函数出错解决方法。—— 改为 cv2.boxPoints()。

​