opencv resize

import numpy as np
import cv2
from cvui import *
WINDOW_NAME = 'CVUI Hello World!'
def main():
    src = cv2.imread("C:\\Users\\chechaojun\\Desktop\\2.jpg")
    INTER_LINEAR = src.copy()
    INTER_LINEAR_EXACT = src.copy()
    INTER_NEAREST = src.copy()
    INTER_CUBIC = src.copy()
    INTER_AREA = src.copy()
    INTER_LANCZOS4 = src.copy()
    INTER_BITS = src.copy()
    INTER_BITS2 = src.copy()
    # Init cvui and tell it to create a OpenCV window, i.e. cv2.namedWindow(WINDOW_NAME).
    cvui.init(WINDOW_NAME)
    floatValue = [2.]
    floatValueLast = [1.]
    max_ = 3
    min_= 0.5
    frame_width = src.shape[1] * max_ * 4
    frame_hight = src.shape[0] + src.shape[0] * max_ * 2 + 100
    frame = np.zeros((frame_hight, frame_width, 3), np.uint8)
    while (True):
        frame[:] = (49, 52, 49)
        cvui.trackbar(frame, src.shape[1] + 20, src.shape[0] / 3, 300, floatValue, min_, max_)
        cvui.image(frame, 0, 0, src)
        if(floatValueLast[0] != floatValue[0]):
            floatValueLast[0] = floatValue[0]
            fx = floatValue[0]
            fy = floatValue[0]
            INTER_LINEAR = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_LINEAR )
            INTER_LINEAR_EXACT = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_LINEAR_EXACT)
            INTER_NEAREST = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_NEAREST )
            INTER_CUBIC = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_CUBIC )
            INTER_AREA = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_AREA )
            INTER_LANCZOS4 = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_LANCZOS4 )
            INTER_BITS = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_BITS)
            INTER_BITS2 = cv2.resize(src,(0, 0), fx = fx, fy = fy, interpolation=cv2.INTER_BITS2)
        y_text= src.shape[0] + 10
        x = 0
        y = y_text + 20
        cvui.text(frame, x, y_text, 'INTER_LINEAR')
        cvui.image(frame, x, y, INTER_LINEAR)
        x += src.shape[1] * max_
        cvui.text(frame, x, y_text, 'INTER_LINEAR_EXACT')
        cvui.image(frame, x, y, INTER_LINEAR_EXACT)
        x += src.shape[1] * max_
        cvui.text(frame, x, y_text, 'INTER_NEAREST')
        cvui.image(frame, x, y, INTER_NEAREST)
        x += src.shape[1] * max_
        cvui.text(frame, x, y_text, 'INTER_CUBIC')
        cvui.image(frame, x, y, INTER_CUBIC)
        y_text += src.shape[0] * max_ + 20
        x = 0
        y = y_text + 20
        cvui.text(frame, x, y_text, 'INTER_AREA')
        cvui.image(frame, 0, y, INTER_AREA)
        x += src.shape[1] * max_
        cvui.text(frame, x, y_text, 'INTER_LANCZOS4')
        cvui.image(frame, x, y, INTER_LANCZOS4)
        x += src.shape[1] * max_
        cvui.text(frame, x, y_text, 'INTER_BITS')
        cvui.image(frame, x, y, INTER_BITS)
        x += src.shape[1] * max_
        cvui.text(frame, x, y_text, 'INTER_BITS2')
        cvui.image(frame, x, y, INTER_BITS2)
        cvui.update()
        cv2.imshow(WINDOW_NAME, frame)
        if cv2.waitKey(20) == 27:
            break
if __name__ == '__main__':
    main()

opencv 可选的插值方式：

1. INTER_LINEAR 线性插值
2. INTER_LINEAR_EXACT
3. INTER_NEAREST 最近邻插值
4. INTER_AREA 区域插值（利用像素区域关系的重采样插值）
5. INTER_CUBIC 三次样条插值（超过4x4像素领域内的双三次插值）
6. INTER_LANCZOS4 Lanczos插值（超过8x8像素邻域的Lanczos插值）
7. INTER_BITS
8. INTER_BITS2

缩小图像一般情况下用INTER_AREA来插值，而若要放大图像，一般情况下用INTER_CUBIC(效率不高，不推荐)或INTER_LINEAR(效率高推荐)

INTER_NEAREST 最近邻插值

从显示效果上看，最近邻插值，是所有插值算法中速度最快的，但不论是放大还是缩小，都有锯齿波
算法：
选取离目标点最近的点作为新的插入点，计算公式为

插值后的边缘效果：由于是以最近的点作为新的插入点，因此边缘不会出现缓慢那的渐慢过度区域，这也导致放大的图像容易出现锯齿现象。

INTER_LINEAR 线性插值

插值后的效果可以有效的避免出现锯齿的现象
算法原理：
线性插值是以距离为权重的一种插值方式。

INTER_AREA 区域插值