How to use OpenCV Library to Convert images to NumPy array In NumPy
OpenCV version from 3.x has DNN and Caffe frameworks, and they are very helpful to solve deep learning problems. It can be installed by using
pip install opencv-contrib-python
cv2 package has the following methods
Python3
import cv2image = cv2.imread('Sample.png')# BGR -> RGBimg = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)cv2.imwrite('opncv_sample.png', img) print (type(img)) |
Output :
<class 'numpy.ndarray'>
How to Convert images to NumPy array?
Images are an easier way to represent the working model. In Machine Learning, Python uses the image data in the format of Height, Width, Channel format. i.e. Images are converted into Numpy Array in Height, Width, Channel format. In this article we will see How to Convert images to NumPy array?
Modules Needed:
- NumPy: By default in higher versions of Python like 3.x onwards, NumPy is available and if not available(in lower versions), one can install by using
pip install numpy
- Pillow: This has to be explicitly installed in later versions too. It is a preferred image manipulation tool. In Python 3, Pillow python library which is nothing but the upgradation of PIL only. It can be installed using
pip install Pillow
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