我有近40000张包含原始像素数据的4D数组中的图像-(示例数量、宽度、高度、通道)。每个图像的宽度为32像素,高度为32像素,RGB颜色有3个通道。我想将它们更改为灰度图像(从3个rgb通道到1个强度通道)。我怎么才能做得很快呢?我的代码:
import pickle
import cv2
training_file = "/train.p"
with open(training_file, mode='rb') as f:
train = pickle.load(f)
X_train = train['features']
def rgb2gray(rgb):
r, g, b = rgb[0], rgb[1], rgb[2]
gray = 0.2989 * r + 0.5870 * g + 0.1140 * b
return gray
X_train_gray = X_train.copy()
for i in range (X_train_gray.shape[0]):
for j in range (X_train_gray.shape[1]):
for k in range (X_train_gray.shape[2]):
rgb = X_train_gray[i,j,k]
gray = rgb2gray(rgb)
X_train_gray[i,j,k] = gray
print("X_train image data shape =", X_train.shape)
print("X_train_grey image data shape =", X_train_gray.shape)
结果:
X_train_grey图像数据形状= (40000,32,32,3)
X_train_grey图像数据形状= (40000,32,32,1)
这很好,但要花很多时间。
我还尝试使用cv2:
X_train_gray = X_train[0].copy()
print("X_train_grey image data shape =", X_train_gray.shape)
X_train_gray = cv2.cvtColor(X_train_gray, cv2.COLOR_BGR2GRAY)
print("X_train_grey image data shape =", X_train_gray.shape)
结果:
X_train_grey图像数据形状= (32,32,3)
X_train_grey图像数据形状= (32,32)
但我失去了强度,不知道如何获得它。
那么,如何快速地将此图像从3通道rgb更改为1通道灰度?
发布于 2019-09-18 22:00:07
如果您可以使用PIL。应该没问题。我有RGB图像并将其转换为:
from PIL import Image
img = Image.open("image_file_path") #for example image size : 28x28x3
img1 = img.convert('L') #convert a gray scale
print(img1.size)
>> (28,28)
但是图像没有通道
y = np.expand_dims(img1, axis=-1)
print(y.shape)
>> (28,28,1)
发布于 2017-02-02 21:13:16
尝试使用:
cv::cvtColor(gray_img,color_img,CV_GRAY2BGR)
https://stackoverflow.com/questions/41966514
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