mmcv/docs/image.md

Image

This module provides some image processing methods, which requires opencv to be installed.

Read/Write/Show

To read or write images files, use imread or imwrite.

import mmcv

img = mmcv.imread('test.jpg')
img = mmcv.imread('test.jpg', flag='grayscale')
img_ = mmcv.imread(img) # nothing will happen, img_ = img
mmcv.imwrite(img, 'out.jpg')

To read images from bytes

with open('test.jpg', 'rb') as f:
    data = f.read()
img = mmcv.imfrombytes(data)

To show an image file or a loaded image

mmcv.imshow('tests/data/color.jpg')
# this is equivalent to

for i in range(10):
    img = np.random.randint(256, size=(100, 100, 3), dtype=np.uint8)
    mmcv.imshow(img, win_name='test image', wait_time=200)

Color space conversion

Supported conversion methods:

• bgr2gray
• gray2bgr
• bgr2rgb
• rgb2bgr
• bgr2hsv
• hsv2bgr

img = mmcv.imread('tests/data/color.jpg')
img1 = mmcv.bgr2rgb(img)
img2 = mmcv.rgb2gray(img1)
img3 = mmcv.bgr2hsv(img)

Resize

There are three resize methods. All imresize_* methods have an argument return_scale, if this argument is False, then the return value is merely the resized image, otherwise is a tuple (resized_img, scale).

# resize to a given size
mmcv.imresize(img, (1000, 600), return_scale=True)

# resize to the same size of another image
mmcv.imresize_like(img, dst_img, return_scale=False)

# resize by a ratio
mmcv.imrescale(img, 0.5)

# resize so that the max edge no longer than 1000, short edge no longer than 800
# without changing the aspect ratio
mmcv.imrescale(img, (1000, 800))

Rotate

To rotate an image by some angle, use imrotate. The center can be specified, which is the center of original image by default. There are two modes of rotating, one is to keep the image size unchanged so that some parts of the image will be cropped after rotating, the other is to extend the image size to fit the rotated image.

img = mmcv.imread('tests/data/color.jpg')

# rotate the image clockwise by 30 degrees.
img_ = mmcv.imrotate(img, 30)

# rotate the image counterclockwise by 90 degrees.
img_ = mmcv.imrotate(img, -90)

# rotate the image clockwise by 30 degrees, and rescale it by 1.5x at the same time.
img_ = mmcv.imrotate(img, 30, scale=1.5)

# rotate the image clockwise by 30 degrees, with (100, 100) as the center.
img_ = mmcv.imrotate(img, 30, center=(100, 100))

# rotate the image clockwise by 30 degrees, and extend the image size.
img_ = mmcv.imrotate(img, 30, auto_bound=True)

Flip

To flip an image, use imflip.

img = mmcv.imread('tests/data/color.jpg')

# flip the image horizontally
mmcv.imflip(img)

# flip the image vertically
mmcv.imflip(img, direction='vertical')

Crop

imcrop can crop the image with one or some regions, represented as (x1, y1, x2, y2).

import mmcv
import numpy as np

img = mmcv.imread('tests/data/color.jpg')

# crop the region (10, 10, 100, 120)
bboxes = np.array([10, 10, 100, 120])
patch = mmcv.imcrop(img, bboxes)

# crop two regions (10, 10, 100, 120) and (0, 0, 50, 50)
bboxes = np.array([[10, 10, 100, 120], [0, 0, 50, 50]])
patches = mmcv.imcrop(img, bboxes)

# crop two regions, and rescale the patches by 1.2x
patches = mmcv.imcrop(img, bboxes, scale_ratio=1.2)

Padding

There are two methods impad and impad_to_multiple to pad an image to the specific size with given values.

img = mmcv.imread('tests/data/color.jpg')

# pad the image to (1000, 1200) with all zeros
img_ = mmcv.impad(img, shape=(1000, 1200), pad_val=0)

# pad the image to (1000, 1200) with different values for three channels.
img_ = mmcv.impad(img, shape=(1000, 1200), pad_val=[100, 50, 200])

# pad the image on left, right, top, bottom borders with all zeros
img_ = mmcv.impad(img, padding=(10, 20, 30, 40), pad_val=0)

# pad the image on left, right, top, bottom borders with different values 
# for three channels.
img_ = mmcv.impad(img, padding=(10, 20, 30, 40), pad_val=[100, 50, 200])

# pad an image so that each edge is a multiple of some value.
img_ = mmcv.impad_to_multiple(img, 32)