# \[YOLO\] YOLODetectObjects example // I want to know about the detected information

**URL:** <https://discourse.processing.org/t/yolo-yolodetectobjects-example-i-want-to-know-about-the-detected-information/31798>\
**Category:** Libraries\
**Created:** [August 19, 2021, 11:48pm UTC](https://discourse.processing.org/t/yolo-yolodetectobjects-example-i-want-to-know-about-the-detected-information/31798 "2021-08-19T23:48:42Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![GWAK](https://avatars.discourse-cdn.com/v4/letter/g/13edae/32.png) [@GWAK](https://discourse.processing.org/u/GWAK)\
**Post date:** [August 19, 2021, 11:48pm UTC](https://discourse.processing.org/t/yolo-yolodetectobjects-example-i-want-to-know-about-the-detected-information/31798/1 "2021-08-19T23:48:42Z")

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> [@Deep Vision - Machine Learning Computer Vision for Processing (Library)](https://discourse.processing.org/t/deep-vision-machine-learning-computer-vision-for-processing-library/30118):
>
> Hello Together I’m happy to present you a project I’ve been working on for over a year now. With OpenCV for Processing we have a good base library for traditional image processing. However, these algorithms are more and more pushed into the background by machine learning. Therefore I started a year ago to develop a library that (mainly) uses the Deep Neural Network (DNN) module of OpenCV to bring machine learning, especially CNN into the Processing world. The library is not about training the…

> **[GitHub - cansik/deep-vision-processing: Deep computer-vision algorithms for...](https://github.com/cansik/deep-vision-processing)**
>
> Deep computer-vision algorithms for the Processing framework. - GitHub - cansik/deep-vision-processing: Deep computer-vision algorithms for the Processing framework.

@cansik / help me.  
 ![pic](https://canada1.discourse-cdn.com/flex036/uploads/processingfoundation1/original/2X/f/f9f88122f52918a98dbd13498a674589a7ff4e8d.jpeg)

As shown in the picture,  
Can I get information about the functions for that library?

ex)  
.hashCode()  
.isSkipNMS()  
.loadLabels(Path)  
.notify()  
…etc

Is there any reference material with coding information?  
Or do you have a site?

help me, please.

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**Author:** ![cansik](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.processing.org/cansik/32/8815_2.png) [@cansik](https://discourse.processing.org/u/cansik)\
**Post date:** [August 20, 2021, 9:11am UTC](https://discourse.processing.org/t/yolo-yolodetectobjects-example-i-want-to-know-about-the-detected-information/31798/2 "2021-08-20T09:11:26Z")

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If you scroll through the readme of the repository, you will find some explanations for the [Object Detection](https://github.com/cansik/deep-vision-processing#object-detection) networks. As mentioned in my post, the documentation is not complete yet, but most of the possibilities are shown in the [various examples](https://github.com/cansik/deep-vision-processing/tree/master/examples). Otherwise I recommend you to go through the [code of the library](https://github.com/cansik/deep-vision-processing/blob/master/src/main/java/ch/bildspur/vision/YOLONetwork.java#L182-L216).

If you have a specific question, feel free to ask it directly.

_Update_:

- `isSkipNMS()` & `setSkipNMS()`: Skips the [non-maximum suppression](https://paperswithcode.com/method/non-maximum-suppression) part of the YOLO output (not recommended)
- `loadLabels()` & `setLabels()`: load from txt file or set the labels (names) for the object detection classes, otherwise only the id of the object class is returned in the result

The other two methods `hashCode()` & `notify()` are java related methods, not defined by the library.

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**Author:** ![GWAK](https://avatars.discourse-cdn.com/v4/letter/g/13edae/32.png) [@GWAK](https://discourse.processing.org/u/GWAK)\
**Post date:** [August 21, 2021, 12:52am UTC](https://discourse.processing.org/t/yolo-yolodetectobjects-example-i-want-to-know-about-the-detected-information/31798/3 "2021-08-21T00:52:15Z")

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@cansik

very very, Thank you.~