<p>I guess that they need so little data because their models are already trained on huge datasets, and they are just transferring the learning (using those pre-trained models as starting point).</p>

CC BY-SA 4.0
2019-08-23T12:16:34.817Z
2019-08-23T12:16:34.817Z
razvanc92
<p>I am wondering why tf object detection api needs so few picture samples for training while regular cnns needs many more?</p>

<p>What I read in tutorials is that tf object detection api needs around 100-500 pictures per class for training (is it true?) while regular CNNs need many many more samples, like tens of thousands or more. Why is it so?</p>

CC BY-SA 4.0
2019-08-22T14:09:36.107Z
I haven't work with the tf object detection api so I might be totally wrong but I guess that they need so little data because their models are already trained on huge datasets, and they are just transferring the learning.
razvanc92
CC BY-SA 4.0
2019-08-22T14:17:39.060Z
You actually might be right :) haven't thought about it, thanks!
GKozinski
CC BY-SA 4.0
2019-08-22T15:26:00.520Z
you are right. Actually from scratch OD needs more images than Classifiers because its a more difficult task
mshlis
CC BY-SA 4.0
2019-08-23T08:54:21.187Z
@razvanc92 you can put your comment as an answer for this question :)
malioboro
<tensorflow><object-detection>
Why tf object detection api needs so few pictures?
GKozinski
# Why tf object detection api needs so few pictures?

(Asked by: username_0 on 2019-08-22)

I am wondering why tf object detection api needs so few picture samples for training while regular cnns needs many more?

What I read in tutorials is that tf object detection api needs around 100-500 pictures per class for training (is it true?) while regular CNNs need many many more samples, like tens of thousands or more. Why is it so?

**Tags:** tensorflow, object-detection

> **Comments:**
> **username_1**: I haven't work with the tf object detection api so I might be totally wrong but I guess that they need so little data because their models are already trained on huge datasets, and they are just transferring the learning.  
> **username_0**: You actually might be right :) haven't thought about it, thanks!  
> **username_2**: you are right. Actually from scratch OD needs more images than Classifiers because its a more difficult task  
> **username_3**: @username_1 you can put your comment as an answer for this question :)  

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## 1 answers

### Answer by username_1 on 2019-08-23. Score: 2 | Accepted answer

I guess that they need so little data because their models are already trained on huge datasets, and they are just transferring the learning (using those pre-trained models as starting point).


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