Evotegra: Extend 100k promo dataset with license plates and faces (R12)

[tmanthey]

Name of Project: Extend 100k promo dataset with license plates and faces

Proposal in one sentence

Extend the round 8 promotional 100k traffic dataset with annotations for licence plates and faces to enable the creation and evaluation of automated anonymization algorithms.

Description of the project and what problem is it solving:

In Ocean DAO Round 8 we commited to create a professional traffic image dataset with at least 100.000 images in ~300 categories and an estimated million objects. The dataset will soon be published on the Ocean Market with an initial data token price of 1 Ocean. The idea is to create promotional datasets that help to establish Ocean Market as a prime source of high quality data.
We propose to extend this promotional dataset next the promised 300 classes with annotations for faces and license plates. By adding these 2 classes we add significant extra value to the dataset which then can be used to train and evaluate automated anonymization algorithms which is an important requirement to assure compliance with privacy regulation such as GDPR.

Category

Unleash data

Metric

Data Consume Volume

What is the final product?

The final product is an extension of the promotional image dataset proposed in DAO round 8 with 2 additional classes “license plates” and “faces”.

Grant Deliverables:

1. Extend the promotional 100k dataset with face annotations
2. Extend the promotional 100k dataset with license plate annotations
3. Provide additional 10000 annotated images

R8 and R10 Deliverables

The attempt to to publish the R8 dataset on Ocean Market was unsuccessful. Due to lack of resources within Ocean Core the issue is unfortunately not going to be fixed prior to the Ocean V4 release. Therefore we put the publishing on hold until Ocean V4 release.
We will provide the annotated images in addition to our R10 grant.

Funding Requested:

3k USD

ROI

We see this effort as a starting point to add other promotional datasets. Our goal is to establish Ocean as a prime source for high quality data. The attractive entry price should encourage many first time users to get familiar with wallets, Ocean tokens and the Ocean Market itself.
Due to the funding restrictions for the unleash data category in R11 we have to limit the number of annotations we can add to the dataset to 5000. By enabling new use cases to train and test automated anonymization algorithms this will notably increase the value of the data.

Proposal Wallet Address:

0x61B15998893cC746B46C08FEdEE13a0d1b33bBa9

Team

Web: www.evotegra.de
Email: manthey@evotegra.de
Twitter: @evotegra
Country of Residence: Germany

Previous OceanDAO Grant?

Yes

[Gareth]

I my view, I think that Ocean needs to focus more on two things that are severely lacking:

1. more people who are actually doing real data science and not just creating apps for data markets or writing reports.

2. actual high quality data sets that are well curated and comprehensive

In terms of Evotegra- this is a genuine team with real credentials in actual engineering in industry and data science. They have the capacity to grow a meaningful carefully curated data set that real data scientists and ML people would actually use. In my view failing to vote for this team is a mistake if you are an ocean holder - these type of teams will actually bring real value and usecases to real data scientists.

[idiom-bytes]

Hi there,

For transparency, starting R12, all proposals will have to be funded within 2 weeks of winning a grant.

The funding deadline is December 27th 23:59 GMT.

You can read our wiki and how to submit a funding request to learn more.

[Takeshi_TGAL]

I am Takeshi from Ocean protocol Japan.
https://twitter.com/oceanprotocolJP

Since Ocean Protocol Japan proposal is bimonthly and not this month, I voted for this project.

Let’s revitalize the Ocean ecosystem together, those of us who have supported Ocean since the dawn of time!

[tmanthey]

We finished our R11 grant we carried over R12. For continuation we propose to the DAO to carry over our R12 grant to R13 for a higher efficiency in the labelling process.