DeOldify is a technique to colorize and restore old black and white images or even film footage. It was developed and is still getting updated by only one person, Jason Antic. It is now the state-of-the-art way to colorize black and white images. Best of all, everything is open-sourced!
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References
- What are GANs: https://youtu.be/ZnpZsiy_p2M
- GitHub with full code, in-depth explanation, and Colabs: https://github.com/jantic/DeOldify
- Free DeepAI image colorization API using DeOldify: https://deepai.org/machine-learning-m...
- MyHeritage colorization tool (the best version of DeOldify available, paid): https://www.myheritage.com/incolor
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Chapters
0:00 - Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise.
0:40 - DeOldify explanation
3:22 - How to use DeOldify Yourself
4:24 - Old Movie Examples
5:06 - Conclusion
Video transcript
00:00
this ai can colorize and restore old
00:03
black and white images and even film
00:05
footage
00:06
this method is called de-aldefy and
00:09
works on pretty much
00:10
any picture if you don't believe me you
00:13
can even try it yourself for free as i
00:15
will show in the video
00:17
but first let's see how it works and
00:19
more amazing results to convince you to
00:22
try it
00:25
[Music]
00:29
this is what's ai and i share artificial
00:31
intelligence news every week
00:33
if you are new to the channel and want
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to stay up to date please consider
00:36
subscribing to not miss any further news
00:40
the aldephi is a technique to colorize
00:42
and restore
00:43
old black and white images or even film
00:45
footage
00:46
it was developed and is still getting
00:48
updated by only one person
00:50
jason antique it is now the
00:53
state-of-the-art way to colorize black
00:55
and white images
00:56
and everything is open sourced but we
00:59
will get back to this in a bit
01:01
first let's see how he achieved that it
01:04
uses a new type of gun training method
01:07
called nogan that he developed himself
01:09
to solve the main problems that appeared
01:11
when training using a normal
01:13
adversarial network architecture
01:15
composed of a discriminator and a
01:17
generator
01:18
typically gun training works by both
01:21
training the discriminator and generator
01:23
at the same time
01:24
where the generator starts by being
01:26
completely random
01:27
and improves over time to fool the
01:29
discriminator
01:30
which tries to tell if the image is
01:32
generated or real
01:34
if this was just completely abstract to
01:36
you i invite you to watch the video i
01:38
made about cans
01:39
in the upper right corner right now and
01:41
linked in the description
01:43
before continuing this video his new
01:46
method
01:46
which he calls the nogan provides the
01:49
same benefits of this usual gun training
01:52
while having to spend way less time
01:54
training the gan architecture
01:56
which is typically pretty heavy in
01:58
computation time
01:59
instead he pre-trains the generator to
02:02
make it already more powerful
02:04
fast and reliable using a regular loss
02:07
function
02:08
this is done by training the generator
02:10
like a regular deep networks
02:12
architecture
02:13
such as resnet that way the model is
02:16
already pretty good at colorizing an
02:18
image
02:18
before training the complete gan
02:20
architecture
02:22
then it only needs a short amount of
02:24
this typical generator discriminator
02:26
gan training to optimize the realism of
02:29
the generated pictures
02:32
gaussian noise is also randomly applied
02:34
to images to generate
02:36
fake noise during training this is a
02:39
type of data augmentation that can be
02:41
performed on the training images to
02:43
improve the results and resistance
02:45
to noisy inputs using the same technique
02:48
as style transfer where the noise will
02:50
be the style of the image we want to
02:52
copy
02:53
and can be applied more or less to the
02:55
transformation
02:57
the whole architecture uses a basic
02:59
resnet backbone
03:00
on a u-net where the generator network
03:02
in the gun training
03:04
is the unet architecture right now
03:07
there is no complete explanation of how
03:09
this works
03:10
but the author is currently working on a
03:13
paper about
03:14
the aldephi where he will further
03:16
investigate
03:17
why and how his technique previously
03:20
found only by trials and errors
03:22
work you can find three things in the
03:25
description of the video
03:27
at first there's the github link with a
03:30
complete detailed explanation of the
03:31
technique and even google collab
03:33
tutorials
03:34
to use it yourself just look at how
03:37
simple this is
03:38
you can just run the few sections enter
03:41
the link of your image
03:43
and run it
04:04
then you can find a free api on deep ai
04:08
using dl defy where you can simply click
04:11
and try yourself
04:13
finally the third link is the most
04:15
advanced version of the aldify if you
04:17
are looking for the best results
04:20
it is on myheritage's website and is
04:23
paid to use
04:24
let's just take a minute to see how it
04:26
works on old movies before ending this
04:40
video
04:50
you better get on the job some of the
04:52
kids may be up this afternoon
04:53
oh jack we can get along without
04:55
dragging those young kids up here oh why
04:57
don't you button up your lip
04:59
you're always squawking about something
05:00
you got more static on the radio
05:07
please leave a like if you went this far
05:09
in the video
05:10
and since there are over 90 of you guys
05:13
watching that are not subscribed yet
05:15
consider subscribing to the channel to
05:17
not miss any further news clearly
05:19
explained
05:20
thank you for watching
05:23
[Music]