Flip array in the up/down direction. Flip the entries in each column in the up/down direction. Rows are preserved, but appear in a different order than before. Equivalent tom[::-1,...]. Does not require the array to be two-dimensional. >>> A = np.diag([1.0, 2, 3])>>>A arr...
fliplr(m)Flip array in the left/right direction.flipud(m)Flip array in the up/down direction.reshape(a, newshape[, order])Gives a new shape to an array without changing its data.roll(a, shift[, axis])Roll array elements along a given axis.rot90(m[, k])Rotate an array by 90 degre...
def flip90_right(arr): new_arr = arr.reshape(arr.size) new_arr = new_arr[::-1] new_arr = new_arr.reshape(arr.shape) new_arr = np.transpose(new_arr)[::-1] return new_arrarr0 = np.array([[1,2,3], [4,5,6], [7,8,9]])flip_180 = flip180(arr0)left_90 = flip90...
flip(np.flip(arr, axis=1), axis=0) 请添加图片描述 向右旋转90度 向右旋转90度,也是向左旋转270度。可以拆解为: 3次向左旋转 1次180度旋转外加1次90度向左旋转 1次90度向左旋转外加1次180度旋转 def flip_right_90_with_left_90(arr): return flip_left_90(flip_left_90(flip_left_90(arr))...
1、在numpy数组中实现“块翻转逻辑”2、反转(翻转)non-square numpy数组的right-left(anti-)diagonals3、使用泛型的数组翻转4、为什么在for循环中,我对字符串数组的索引有一半有效,但最后一半无效?5、翻转或旋转一维数组 🐸 相关教程4个 1、NumPy 入门教程2、Python 进阶应用教程3、Python 办公自动化教程4、Pytho...
shape[1] // crop_ratio # Extract the focused part using array slicing focused_part = image[top:bottom, left:right] return focused_part display(crop_image(reduced_M, 4, 2)) 5、RGB通道 代码语言:javascript 代码运行次数:0 运行 AI代码解释 def RGB_image(image,image_color): if image_color ...
Flip arrayinthe left/right direction.也就是说进行`列对换`Equivalent to m[:,::-1]. Requires the array to be at least2-D(二维).Examples--->>> A = np.diag([1.,2.,3.])>>> Aarray([[1.,0.,0.],[0.,2.,0.],[0.,0.,3.]])>>> np.fliplr(A)array([[0.,0.,1.],[...
The numpy.fliplr() function is used to flip array in the left/right direction. Flip the entries in each row in the left/right direction. Columns are preserved, but appear in a different order than before. This function is particularly useful for image processing tasks such as flipping an im...
top =image.shape[0]// crop_ratiobottom = zoom_ratio * image.shape[0]// crop_ratioleft = image.shape[1]// crop_ratioright = zoom_ratio * image.shape[1]// crop_ratio# Extract the focused partusingarray slicing focused_part = image[top:bottom, left:right]returnfocused_partdisplay(crop...
right = zoom_ratio * image.shape[1] // crop_ratio # Extract the focused part using array slicing focused_part = image[top:bottom, left:right] return focused_part display(crop_image(reduced_M, 4, 2)) 5、RGB通道 def RGB_image(image,image_color): ...