SciPy初学者(day one)
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2022-07-12 22:19:15
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NumPy提供了一个高性能的多维数组和基本工具来计算和操作这些数组,SciPy提供了许多运行的函数
首先,我们来看一下图像操作
SciPy提供一些处理图片的基础功能,例如 他把图片从磁盘中读取出来到NumPy数组中,将NumPy数组
作为图片传入磁盘以调整图片的大小,
from scipy.misc import imread, imsave, imresize
# Read an JPEG image into a numpy array
img = imread('assets/cat.jpg')
print(img.dtype, img.shape) # Prints "uint8 (400, 248, 3)"
# We can tint the image by scaling each of the color channels
# by a different scalar constant. The image has shape (400, 248, 3);
# we multiply it by the array [1, 0.95, 0.9] of shape (3,);
# numpy broadcasting means that this leaves the red channel unchanged,
# and multiplies the green and blue channels by 0.95 and 0.9
# respectively.
img_tinted = img * [1, 0.95, 0.9]
# Resize the tinted image to be 300 by 300 pixels.
img_tinted = imresize(img_tinted, (300, 300))
# Write the tinted image back to disk
imsave('assets/cat_tinted.jpg', img_tinted)
以下是他的效果图
在处理这个图片的时候,出现了各种问题
- SciPy 1.2.0中将imread改成了imageio.imread 还有将imresize改成skimage.transform.resize
- 图片地址还需要你自己修改
这只是基础的功能,还有一些其他的功能需要大家去看文档
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