<p>It is actually very easy, I didn't know the solution would be that simple.
With opencv, you can do :</p>
<pre><code>resized_roi= cv2.resize(roi, (224,224)) 
</code></pre>
<p>and that's it :]</p>

CC BY-SA 4.0
2021-06-17T14:16:50.613Z
2021-06-17T14:16:50.613Z
Valentin
<p>As English is not my native language, I have some hard time understanding the following sentence:</p>
<blockquote>
<p>Regardless of the size or aspect ratio of the candidate region, we warp all pixels in a tight bounding box around it to the required size. Prior to warping, we dilate the tight bounding box so that at the warped size there are exactly p pixels of warped image context around the original box (we use p = 16).</p>
</blockquote>
<p>This is from <a href="https://arxiv.org/pdf/1311.2524.pdf#page=3" rel="nofollow noreferrer">the R-CNN paper</a>. I already extracted the ROI, but now, they say that the input of the CNN should be 227 x 227, but a lot of my ROIs are much smaller. How can I deal with it?</p>

CC BY-SA 4.0
2021-06-21T23:26:55.617Z
Hello. I am still not sure if your question was theoretical/conceptual or practical (programming issue), but I would like to note that programming issues are generally off-topic here. See https://ai.stackexchange.com/help/on-topic for more details.
nbro
<deep-learning><papers><object-detection><r-cnn>
What to do when the ROIs are smaller than $227 \times 227$ in R-CNN?
Valentin
# What to do when the ROIs are smaller than $227 \times 227$ in R-CNN?

(Asked by: username_0 on 2021-06-17)

As English is not my native language, I have some hard time understanding the following sentence:

> Regardless of the size or aspect ratio of the candidate region, we warp all pixels in a tight bounding box around it to the required size. Prior to warping, we dilate the tight bounding box so that at the warped size there are exactly p pixels of warped image context around the original box (we use p = 16).

This is from [the R-CNN paper](https://arxiv.org/pdf/1311.2524.pdf#page=3). I already extracted the ROI, but now, they say that the input of the CNN should be 227 x 227, but a lot of my ROIs are much smaller. How can I deal with it?

**Tags:** deep-learning, papers, object-detection, r-cnn

> **Comments:**
> **username_1**: Hello. I am still not sure if your question was theoretical/conceptual or practical (programming issue), but I would like to note that programming issues are generally off-topic here. See https://ai.stackexchange.com/help/on-topic for more details.  

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## 1 answers

### Answer by username_0 on 2021-06-17. Score: 2 | Accepted answer

It is actually very easy, I didn't know the solution would be that simple.
With opencv, you can do :
resized_roi= cv2.resize(roi, (224,224)) 

and that's it :]


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