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If I have image with shape (height, width, num_channel) and I want to compute mean:
numpy
mean=np.mean(x)
If num_channels = 3, I can use OpenCV:
mean=np.mean(cv2.mean(x)[:3])
OpenCV computes mean per channel for RGBA images returning for RGB images array (mean_channel_0, mean_channel_1, mean_2, 0) and we use np.mean() to take average of that.
First works for any shape but slower
Second works for images with 3 channels, but faster
Request:
mean operation that
works on any shape
is faster than OpenCV or numpy version
Can you contribute to the implementation?
I can contribute
Is your feature request specific to a certain interface?
It applies to everything
Contact Details
No response
Is there an existing issue for this?
I have searched the existing issues
Code of Conduct
I agree to follow this project's Code of Conduct
The text was updated successfully, but these errors were encountered:
Describe what you are looking for
If I have image with shape
(height, width, num_channel)
and I want to compute mean:numpy
If num_channels = 3, I can use OpenCV:
OpenCV computes mean per channel for RGBA images returning for RGB images array
(mean_channel_0, mean_channel_1, mean_2, 0)
and we usenp.mean()
to take average of that.First works for any shape but slower
Second works for images with 3 channels, but faster
Request:
mean operation that
Can you contribute to the implementation?
Is your feature request specific to a certain interface?
It applies to everything
Contact Details
No response
Is there an existing issue for this?
Code of Conduct
The text was updated successfully, but these errors were encountered: