<p>One answer is infinite amount of time because it can always be better.</p>
<p>Another answer is:</p>
<ul>
<li>10k for training set</li>
<li>A PC with a GPU (3~4k USD), google colab (10 USD per month), or other cloud service (probably more expensive than colab)</li>
<li>One developer, 1 day lol</li>
<li>Two kinds is easier than multiple kinds</li>
<li>There is no paper that seeks to answer your question the way you put it. I wouldn't even recommend a paper. In fact, for you I'd recommend an AutoML tutorial. Check <a href="https://towardsdatascience.com/top-8-no-code-machine-learning-platforms-you-should-use-in-2020-1d1801300dd0" rel="nofollow noreferrer">these</a>. * no offence if I've misjudged your knowledge/skill level.</li>
<li>Here's a paper anyway :) <a href="https://paperswithcode.com/lib/torchvision/alexnet" rel="nofollow noreferrer">https://paperswithcode.com/lib/torchvision/alexnet</a></li>
</ul>
<p>To conclude, please be aware that your question is super open ended, and my answer is bad (but good enough for now maybe), but a good answer doesn't really exist. It's always going to be context dependent. For instance, you never said whether you need 90% or 99% accuracy.</p>

CC BY-SA 4.0
2021-12-27T09:56:18.577Z
Your answer is perfect, the question was intentionally open, you provided a real life example.
bokan
CC BY-SA 4.0
2021-03-23T17:57:50.627Z
2021-03-23T17:57:50.627Z
Alexander Soare
<p>I would like to have an order of magnitude of ressources required to build an image recognition system.</p>
<p>Let say you want to build a startup company which main product will have to distinguish 20 different kinds of objects (bottle, dogs, car, flowers...). Images are already tagged.</p>
<ul>
<li>How many images are needed as a learning set ? 1k, 10k, 100k, 1
million ?</li>
<li>What kind of hardware and how long will the learning process take ?</li>
<li>How many developers, how much time ​?</li>
<li>Does it changes a lot if the number of target output is reduced to two kinds, or increased to one thousands ?</li>
</ul>
<p>​A link to a real life paper would be perfect. Thank you</p>

CC BY-SA 4.0
2021-12-27T09:54:52.987Z
"Closed. This question needs to be more focused. It is not currently accepting answers." How stupid is that ? I ask for an order of magnitude or a real life example. Of course it is not focused !
bokan
<image-processing><hardware-evaluation>
What amount of ressources is involved in building an image recognition system?
bokan
# What amount of ressources is involved in building an image recognition system?

(Asked by: username_0 on 2021-03-17)

I would like to have an order of magnitude of ressources required to build an image recognition system.

Let say you want to build a startup company which main product will have to distinguish 20 different kinds of objects (bottle, dogs, car, flowers...). Images are already tagged.

* How many images are needed as a learning set ? 1k, 10k, 100k, 1
  million ?
* What kind of hardware and how long will the learning process take ?
* How many developers, how much time ​?
* Does it changes a lot if the number of target output is reduced to two kinds, or increased to one thousands ?

​A link to a real life paper would be perfect. Thank you

**Tags:** image-processing, hardware-evaluation

> **Comments:**
> **username_0**: "Closed. This question needs to be more focused. It is not currently accepting answers." How stupid is that ? I ask for an order of magnitude or a real life example. Of course it is not focused !  

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## 1 answers

### Answer by username_1 on 2021-03-23. Score: 3 | Accepted answer

One answer is infinite amount of time because it can always be better.

Another answer is:

* 10k for training set
* A PC with a GPU (3~4k USD), google colab (10 USD per month), or other cloud service (probably more expensive than colab)
* One developer, 1 day lol
* Two kinds is easier than multiple kinds
* There is no paper that seeks to answer your question the way you put it. I wouldn't even recommend a paper. In fact, for you I'd recommend an AutoML tutorial. Check [these](https://towardsdatascience.com/top-8-no-code-machine-learning-platforms-you-should-use-in-2020-1d1801300dd0). \* no offence if I've misjudged your knowledge/skill level.
* Here's a paper anyway :) <https://paperswithcode.com/lib/torchvision/alexnet>

To conclude, please be aware that your question is super open ended, and my answer is bad (but good enough for now maybe), but a good answer doesn't really exist. It's always going to be context dependent. For instance, you never said whether you need 90% or 99% accuracy.

> **Comments:**
> **username_0**: Your answer is perfect, the question was intentionally open, you provided a real life example.  

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