是否可以为 RGB 和灰度图像创建训练矩阵

Question

I'm trying to create training matrix for CNN. Images are both RGB and Grey/scale.

To create something like [ # of images, #features ]

Image Size is :

1024* 1024

Following is my code:

from skimage.transform import rescale, resize
from skimage import io

features = np.empty((0,1024 * 1024), np.float32)
imagePath = directoyPath+"/"+ imageName
image = io.imread(imagePath)
print(image.shape)
flatFeatures = np.reshape(image,(1,1024*1024))
print(flatFeatures.shape)
features = np.append(features, flatFeatures, axis=0)
print(features.shape)

The problem is RGB shape is (1024,1024,3).

How i can feed the RGB and grey scale images to features matrix.

Answer 1

simply you would have to feed in the RGB images after converting it into greyscale, you cannot pass images of different channels into a CNN, since RGB have 3 channels and grey scale images have 1 channel, specifying channels in the input layer of a CNN are necessary, it cannot be dynamic, so you have to make sure that you either have 3 channels or 1

for your purposes i would suggest you convert your grayscale images to RGB using cvtColor(gray, color, cv::COLOR_GRAY2BGR) the image wouldn't actually gain any color, but the number of channels in it would be 3, allowing you to pass both RGB and grayscale(technically RGB but still colorless) images together