<p><strong>APsmall</strong> stands for <strong>Average Precision for small objects</strong>.</p>
<hr />
<p>This website contains all the descriptions about the metrics:
<a href="https://cocodataset.org/#detection-eval" rel="nofollow noreferrer">https://cocodataset.org/#detection-eval</a></p>
<p>If you want to know more about the metrics evaluation (how to calculate this metric), you can find the metric's source code here: <a href="https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py" rel="nofollow noreferrer">https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py</a></p>

CC BY-SA 4.0
2021-08-17T19:42:55.510Z
2021-08-17T19:42:55.510Z
Andre Goulart
<blockquote>
<p>Does it mean that there are no small objects in my dataset to be detected?</p>
</blockquote>
<p>Yes.</p>
<p>From the evaluation source code as mentioned by the other answer, <a href="https://github.com/cocodataset/cocoapi/blob/8c9bcc3cf640524c4c20a9c40e89cb6a2f2fa0e9/PythonAPI/pycocotools/cocoeval.py#L334" rel="nofollow noreferrer">L334</a>:</p>
<blockquote>
<p>-1 for the precision of absent categories</p>
</blockquote>
<p>From the coco dataset website, <a href="https://cocodataset.org/#detection-eval" rel="nofollow noreferrer">Detection Evaluation</a>:</p>
<blockquote>
<p><span class="math-container">$AP_{small}$</span>: AP for small objects: area &lt; <span class="math-container">$32^{2}$</span><br />
<span class="math-container">$AP_{medium}$</span>: AP for medium objects: <span class="math-container">$32^{2}$</span> &lt; area &lt; <span class="math-container">$96^{2}$</span><br />
<span class="math-container">$AP_{large}$</span>: AP for large objects: area &gt; <span class="math-container">$96^{2}$</span></p>
</blockquote>

CC BY-SA 4.0
2023-08-30T19:59:45.870Z
2023-08-30T19:59:45.870Z
IndefiniteBen
<p>I am training some Object-Detection-Models from the TensorFlow Object Detection API and got from the evaluation with MS COCO metrics the following results for Average Precision:</p>
<p>IoU = 0.5;0.9
maxDets = 100
area = small
AP = -1.000</p>
<p>The other values all make sense to me. But I don´t know what the -1.000 stands for. Does it mean that there are no small objects in my dataset to be detected?</p>

<deep-learning><convolutional-neural-networks><object-detection><testing><precision>
What does a value of -1.000 mean in MS COCO Metrics for Object Detection
Benjamin Stecker
# What does a value of -1.000 mean in MS COCO Metrics for Object Detection

(Asked by: username_0 on 2021-08-17)

I am training some Object-Detection-Models from the TensorFlow Object Detection API and got from the evaluation with MS COCO metrics the following results for Average Precision:

IoU = 0.5;0.9
maxDets = 100
area = small
AP = -1.000

The other values all make sense to me. But I don´t know what the -1.000 stands for. Does it mean that there are no small objects in my dataset to be detected?

**Tags:** deep-learning, convolutional-neural-networks, object-detection, testing, precision


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## 2 answers

### Answer by username_1 on 2021-08-17. Score: 0

**APsmall** stands for **Average Precision for small objects**.

---

This website contains all the descriptions about the metrics:
<https://cocodataset.org/#detection-eval>

If you want to know more about the metrics evaluation (how to calculate this metric), you can find the metric's source code here: <https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py>


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### Answer by username_2 on 2023-08-30. Score: 0

> Does it mean that there are no small objects in my dataset to be detected?

Yes.

From the evaluation source code as mentioned by the other answer, [L334](https://github.com/cocodataset/cocoapi/blob/8c9bcc3cf640524c4c20a9c40e89cb6a2f2fa0e9/PythonAPI/pycocotools/cocoeval.py#L334):

> -1 for the precision of absent categories

From the coco dataset website, [Detection Evaluation](https://cocodataset.org/#detection-eval):

> $AP\_{small}$: AP for small objects: area < $32^{2}$  
> $AP\_{medium}$: AP for medium objects: $32^{2}$ < area < $96^{2}$  
> $AP\_{large}$: AP for large objects: area > $96^{2}$


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