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
```