一、Opencv官方文档中resize的描述：
resize
Resizes an image.
C++: void resize(InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR )
Python: cv2.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]]) → dst
C: void cvResize(const CvArr* src, CvArr* dst, int interpolation=CV_INTER_LINEAR )
Python: cv.Resize(src, dst, interpolation=CV_INTER_LINEAR) → None
Parameters:
src – Source image.
dst – Destination image. It has the size dsize (when it is non-zero) or the size computed from src.size() , fx , and fy . The type of dst is the same as of src .
dsize –
Destination image size. If it is zero, it is computed as:
//在下文fx和fy的计算方式中可以看到，fx表达横向的放缩倍数，fy表达纵向的放缩倍数，dsize表达放缩后的图像的横和纵向长度
dsize = Size(round(fxsrc.cols), round(fysrc.rows))
Either dsize or both fx and fy must be non-zero.
fx –
Scale factor along the horizontal axis. When it is 0, it is computed as
(double)dsize.width/src.cols
//fx表达横向的放缩倍数
fy –
Scale factor along the vertical axis. When it is 0, it is computed as
(double)dsize.height/src.rows
//fy表达纵向的放缩倍数
interpolation –
Interpolation method:
INTER_NEAREST - a nearest-neighbor interpolation
INTER_LINEAR - a bilinear interpolation (used by default)
INTER_AREA - resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire’-free results. But when the image is zoomed, it is similar to the INTER_NEAREST method.
INTER_CUBIC - a bicubic interpolation over 4x4 pixel neighborhood
INTER_LANCZOS4 - a Lanczos interpolation over 8x8 pixel neighborhood
The function resize resizes the image src down to or up to the specified size. Note that the initial dst type or size are not taken into account. Instead, the size and type are derived from the src,dsize,fx , and fy . If you want to resize src so that it fits the pre-created dst , you may call the function as follows:
// explicitly specify dsize=dst.size(); fx and fy will be computed from that.
resize(src, dst, dst.size(), 0, 0, interpolation);
If you want to decimate the image by factor of 2 in each direction, you can call the function this way:
// specify fx and fy and let the function compute the destination image size.
resize(src, dst, Size(), 0.5, 0.5, interpolation);
To shrink an image, it will generally look best with CV_INTER_AREA interpolation, whereas to enlarge an image, it will generally look best with CV_INTER_CUBIC (slow) or CV_INTER_LINEAR (faster but still looks OK).
See also warpAffine(), warpPerspective(), remap()
二、使用该函数：
1、原图：shape=(333,500,3)
2、将图像按比例缩小：
import cv2img = cv2.imread("bird.jpg")
height, width, channel = img.shapesize_decrease = (int(width/2), int(height/2))
img_decrease = cv2.resize(img,size_decrease,interpolation=cv2.INTER_CUBIC)
cv2.imwrite("bird_decrease.jpg",img_decrease)
3、将图像按比例放大：
import cv2img = cv2.imread("bird.jpg")
height, width, channel = img.shapesize_increase = (int(width*2), int(height*2))
img_increase = cv2.resize(img,size_increase,interpolation=cv2.INTER_CUBIC)
cv2.imwrite("bird_increase.jpg",img_increase)
4、按照指定大小缩小：
img_required_dec = cv2.resize(img,(200,150),interpolation=cv2.INTER_CUBIC)
cv2.imwrite("bird_required_dec.jpg", img_required_dec)
5、按照指定大小放大：
img_required_inc = cv2.resize(img, (600,500),interpolation=cv2.INTER_CUBIC)
cv2.imwrite("bird_required_inc.jpg", img_required_inc)
三、探究interpolation参数的不同形式对resize结果的影响：
1、INTER_NEAREST：
img_NEAREST = cv2.resize(img,(img.shape[1],img.shape[0]),interpolation=cv2.INTER_NEAREST)cv2.imwrite("bird_NEAREST.jpg", img_NEAREST)
2、INTER_LINEAR：
img_LINEAR = cv2.resize(img,(img.shape[1],img.shape[0]),interpolation=cv2.INTER_LINEAR)cv2.imwrite("bird_LINEAR.jpg", img_LINEAR)
3、INTER_AREA：
img_AREA = cv2.resize(img,(img.shape[1],img.shape[0]),interpolation=cv2.INTER_AREA)cv2.imwrite("bird_AREA.jpg", img_AREA)4、INTER_CUBIC：
img_CUBIC = cv2.resize(img,(img.shape[1],img.shape[0]),interpolation=cv2.INTER_CUBIC)cv2.imwrite("bird_CUBIC.jpg", img_CUBIC)
5、INTER_LANCZOS4：
img_LANCZOS4 = cv2.resize(img,(img.shape[1],img.shape[0]),interpolation=cv2.INTER_LANCZOS4)cv2.imwrite("bird_LANCZOS4.jpg", img_LANCZOS4)
结论：肉眼看没有什么区别
三、opencv官方文档中对不同形式的interpolation进行解读：
1、INTER_NEAREST:
最近邻插值
2、INTER_LINEAR:
线性插值（默认使用）
3、INTER_AREA:
利用像素区域关系进行重新采样。因为它给出了moire’-free的结果，所以在图像抽取(decimation)中更偏向于使用它。但是在图像放大(zoomed)中，它和INTER_NEAREST方式比较相似。
4、INTER_CUBIC:
在4x4像素邻域中bicubic插值
5、INTER_LANCZOS4:
在8x8像素邻域中Lanczos插值
四、该函数使用的注意事项：
1、dsize的数据类型必须为Integer
2、.jpg格式的图像使用cv2的imread读取后，其shape形式为(height,width,channel)
3、cv2的resize函数使用的dsize其格式为(width,height)，和读取格式相反
五、疑问：
1、在opencv官方文档中，cv.resize函数返回值为None。但是实际使用中，resize函数返回了改变大小后的图像。为什么会有这样的不同？（见更新）
2、cv.resize的参数为src,dst,dsize,fx,fy,interpolation，这些参数是可选的吗？比如，设定了fx和fy后就可以不必设定dsize吗？
3、各个插值方式的细节、使用场景以及为什么要选择该插值方式。
更新：
1、在Opencv官方文档中，给出了C、C++、Python三种语言的同一函数的不同形式。其中，Python给出了两种形式：
（1）cv.Resize：
Python: cv.Resize(src, dst, interpolation=CV_INTER_LINEAR) → None
该函数是被官方文档标注Legacy Python fuction，是opencv的遗留函数，已经不再使用了，其返回值为None
（2）cv2.resize：
Python: cv2.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]]) → dst
是cv.Resize更新后的函数，返回值是dst，不是None
在opencv官方文档中，cv.Resize函数返回值为None；cv2.Resize函数返回值是dst。实际使用的是cv2.resize，该函数的返回值为resize后的图像。
2、opencv官方文档中的search很好用！(like
