Being able to identify individual animals is a critical aspect of modern conservation. In the case of sea turtle conservation efforts, tracking where and when individuals are spotted can help reveal patterns of movement and residency, and allow more accurate estimates of population. Sea turtles can be identified using their facial scales, which are as unique as a human fingerprint.

Local Ocean Conservation (LOC) would like to use the unique fingerprint of turtle faces to integrate facial image recognition into their existing turtle applications, which would speed up many routine conservation tasks. As a first step towards such a system, we need to develop a tool that can crop a given image to show only the important facial region, reducing the chances of an accidental match down the line.

The goal of this competition is to develop an algorithm or model that can take in an image of a sea turtle and output the position of a bounding box around that all-important scale pattern. A labelled training set with bounding box annotations has been provided.

About Local Ocean Conservation (LOC) (localocean.co):

LOC is a private, not-for-profit organisation committed to the protection of Kenya’s marine environment. LOC supports the communities and coastal areas in Watamu and Diani, Kilifi County with marine conservation and community development projects – centred around a holistic approach to conservation. LOC has been doing marine conservation for over 20yrs.

The evaluation metric for this competition is Intersection-over-Union (IoU - more information on this metric in this article: https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for-object-detection/)

You must specify the extent of the bounding box as shown in the sample submission file, specifying x, y, width and height as floats between 0 and 1 (fractions of the image extent). The bounding box coordinates in pixels are:

x1, y1, x2, y2 = (x*image_width), (y*image_height), ((x+w)*image_width), ((y+h)*image_height)

The starter notebook contains an example showing how to generate an image like the one above to check that your bounding box looks good.

Your submission file should look like this:

Image_ID          x       y      w     h

4863D911        0.41     0.98   0.12  0.34
6DD3ADD5        0.23     0.61   0.12   0.01

This is a learning competition. Aside from knowledge, there are no prizes for this competition.

You will receive 25 points for your first submission and 50 points for your first non-sample submission. You can read more about Zindi points here.

As this is a knowledge competition it will not close.

We reserve the right to update the contest timeline if necessary.

🚀 What to know to get started with Zindi Challenges

How to get started on Zindi

How to create a team on Zindi

How to run notebooks in Colab

How to update your profile

As this is a learning challenge, aside from the rules in the Terms of Use, no other particular rules apply.

This challenge is open to all and not restricted to any country.

Teams and collaboration

You may participate in this competition as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the highest number of submissions among team members at team formation.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be disqualified.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted.

If the challenge is a computer vision challenge, image metadata (Image size, aspect ratio, pixel count, etc) may not be used in your submission.

You may use pretrained models as long as they are openly available to everyone.

The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party.

Submissions and winning

You may make a maximum of 10 submissions per day.

Note that to count, your submission must first pass processing. If your submission fails during the processing step, it will not be counted and not receive a score; nor will it count against your daily submission limit. If you encounter problems with your submission file, your best course of action is to ask for advice on the Competition’s discussion forum.

Note that there is no public/private leaderboard split for this challenge. Read more about public and private leaderboards in this post.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Zindi also reserves the right to disqualify you and/or your submissions from any competition if we believe that you violated the rules or violated the spirit of the competition or the platform in any other way. The disqualifications are irrespective of your position on the leaderboard and completely at the discretion of Zindi.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.