Python opencv cv2.applyColorMap 伪色彩函数

在图像处理中，伪色彩用途广泛。在OpenCV库中，常见的伪色彩模式都可通过cv2.applyColorMap(src, userColor[, dst])直接调用，很是方便快捷。例如伪色彩中的COLORMAP_JET模式，就常被用于生成我们所常见的热力图：import cv2# COLORMAP_AUTUMN = 0,# COLORMAP_BONE = 1,# COLORMAP_JET = 2,#

hxxjxw

11128人浏览 · 2022-01-12 15:48:15

hxxjxw · 2022-01-12 15:48:15 发布

在图像处理中，伪色彩用途广泛。OpenCV的定义12种colormap（色度图），可以应用于灰度图像(即单通道)，使用函数applycolormap产生伪彩色图像。

即我们画图的时候，得到的attention map一般是单通道的，这样用plt.imshow()可以画，但是用cv2就不行了，它要求3通道的。用cv2.applyColorMap()可以合理转化成3通道

cv2.applyColorMap(src, userColor[, dst])

例如伪色彩中的 COLORMAP_JET模式，就常被用于生成我们所常见的 热力图：

import cv2

# COLORMAP_AUTUMN = 0,
# COLORMAP_BONE = 1,
# COLORMAP_JET = 2,
# COLORMAP_WINTER = 3,
# COLORMAP_RAINBOW = 4,
# COLORMAP_OCEAN = 5,
# COLORMAP_SUMMER = 6,
# COLORMAP_SPRING = 7,
# COLORMAP_COOL = 8,
# COLORMAP_HSV = 9,
# COLORMAP_PINK = 10,
# COLORMAP_HOT = 11

img = cv2.imread("wave.jpg")
for i in range(0, 13):
    im_color = cv2.applyColorMap(img, i)
    cv2.imwrite("wave_{}.jpg".format(i), im_color)

import matplotlib.cm as mpl_color_map
import cv2
import numpy as np
import matplotlib.pyplot as plt
import torch, copy, os
from torchvision import transforms
from PIL import Image

#code is from https://github.com/innovation-cat/pytorch_cnn_visualization_implementations/blob/master/utils.py
def apply_colormap_on_image(org_im, activation, colormap_name):
	"""
		Apply heatmap on image
	Args:
		org_img (PIL img): Original image
		activation_map (numpy arr): Activation map (grayscale) 0-255
		colormap_name (str): Name of the colormap
	"""
	# Get colormap
	color_map = mpl_color_map.get_cmap(colormap_name)
	no_trans_heatmap = color_map(activation)
	# Change alpha channel in colormap to make sure original image is displayed
	heatmap = copy.copy(no_trans_heatmap)
	heatmap[:, :, 3] = 0.4
	heatmap = Image.fromarray((heatmap*255).astype(np.uint8))
	no_trans_heatmap = Image.fromarray((no_trans_heatmap*255).astype(np.uint8))

	# Apply heatmap on iamge
	heatmap_on_image = Image.new("RGBA", org_im.size)
	heatmap_on_image = Image.alpha_composite(heatmap_on_image, org_im.convert('RGBA'))
	
	#heatmap = heatmap.transpose(method=Image.TRANSVERSE)
	print(heatmap_on_image)
	print(heatmap)
	
	heatmap_on_image = Image.alpha_composite(heatmap_on_image, heatmap)
	return no_trans_heatmap, heatmap_on_image