Got some questions
1 : how do we calculate the mean?
pseudo codes: mean is the average of all of the image
for img in imagenet_imgs: (b,g,r) = img[:3]; mean.b += b.mean(); // add all of the pixels of b channels and divide it by pixels size of b channel mean.g += g.mean(); mean.r += r.mean(); mean /= len(imagenet_imgs);
or pseudo codes: mean is the mean of single image
(b,g,r) = img[:3]; mean.b = b.mean(); mean.g = g.mean(); mean.r = r.mean();
I think the mean mentioned by lesson 3 is the first case–mean is the average of all of the image
When we training, we do it like following codes?
for img in batches: img -= mean img/=255
2 : Anybody ever tried to ignore the mean of the image?
3 : Lesson 3 said animation are very different compare with real world photo, if I want to train some animation
classifier, I better find out the mean by myself?
4 : Could we subtract the mean of the image as following?
for img in batches: //rather than subtract the mean of all datasets, subtract the mean of each image img -= img.mean(); img/=255