# A light weight model to detect website logo form website screenshots
**URL:** https://community.ultralytics.com/t/a-light-weight-model-to-detect-website-logo-form-website-screenshots/617
**Category:** Discussion
**Tags:** question, support
**Created:** [December 19, 2024, 12:57pm UTC](https://community.ultralytics.com/t/a-light-weight-model-to-detect-website-logo-form-website-screenshots/617 "2024-12-19T12:57:24Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@a6kme](https://community.ultralytics.com/u/a6kme)
#### Post date: [December 19, 2024, 12:57pm UTC](https://community.ultralytics.com/t/a-light-weight-model-to-detect-website-logo-form-website-screenshots/617/1 "2024-12-19T12:57:24Z")
Hello,
I want to create a light weight model which can preferably run in the browser, and detect website logo from the website screenshots.
Example:
Here are the things that I have tried so far. Would be great if I can get some feedbacks on whether I am approaching this right.
I am exploring variants of YOLO for my use case. Since the model is trained on COCO dataset, I won’t be able to infer using zero shot. I will have to fine tune the model. I am using ultralytics APIs to train the model.
For dataset, I could not find similar dataset on internet, which has website screenshot with annotated logos, so I am thinking of creating one myself for top 100 websites. I am not sure if this data will be sufficient, but I can try to get started and see how the performance looks like.
I am using roboflow to annotate the images and the download the dataset so that I can train my YOLO model.
My questions are: Is this the right approach or are there better approach to this problem?
Thanks!
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### Author:  [@Toxite](https://community.ultralytics.com/u/Toxite)
#### Post date: [December 19, 2024, 1:13pm UTC](https://community.ultralytics.com/t/a-light-weight-model-to-detect-website-logo-form-website-screenshots/617/2 "2024-12-19T13:13:42Z")
Have you tried YOLO World?
> **[YOLO-World (Real-Time Open-Vocabulary Object Detection)](https://docs.ultralytics.com/models/yolo-world/)**
>
> Explore the YOLO-World Model for efficient, real-time open-vocabulary object detection using Ultralytics YOLOv8 advancements. Achieve top performance with minimal computation.
You can also fine-tune it.
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### Author:  [@a6kme](https://community.ultralytics.com/u/a6kme)
#### Post date: [December 20, 2024, 7:37am UTC](https://community.ultralytics.com/t/a-light-weight-model-to-detect-website-logo-form-website-screenshots/617/3 "2024-12-20T07:37:40Z")
@Toxite - No, I have not. Thank you for your suggestion. I will give it a try. 🙂
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### Author:  [@BurhanQ](https://community.ultralytics.com/u/BurhanQ)
#### Post date: [December 20, 2024, 11:35am UTC](https://community.ultralytics.com/t/a-light-weight-model-to-detect-website-logo-form-website-screenshots/617/4 "2024-12-20T11:35:40Z")
There are also lots of existing logo datasets you can start from. They might not have _precisely_ what you’re looking for, but it could be helpful to include as a start. Additionally, if you find logos that have an alpha channel (transparent background) you can generate a lot of example images by placing them on various images (same with ones that have an opaque background, but I guess that depends on the brand).
An example dataset from searching “website logo dataset” [https://weblogo2m.github.io/](https://weblogo2m.github.io/)