This challenge was designed specifically for the AI Tunisia Hack 2019, which takes place from 20 to 22 September. Welcome to the AI Tunisia Hack participants!

After AI Hack Tunisia, this competition will be re-opened as a Knowledge Challenge to allow others in the Zindi community to learn and test their skills.

Vehicle License plate detection and recognition is a well-known challenge that has been tackled by many computer-vision labs and companies. However, each country has its own specific license plate formats. This challenge is targeting regular Tunisian license plates. The data provided for this challenge is composed of two datasets:

• A set of vehicle images (900 images) taken from the internet and annotated manually. The annotations are the coordinates of the bounding box containing the license plate.
• A set of license plate images (900 images) where the annotations are the text written in the license plate.

This challenge was designed by InstaDeep in Tunisia in partnership with the National Road Safety Observatory of Tunisia, specifically for the AI-Hack-Tunisia 2019 hackathon.

The objective of this challenge is to detect the vehicle’s license plates then recognize the characters in each license plate. The solution will then be used to detect vehicle license plates in traffic cameras.

To read more about the National Road Safety Observatory of Tunisia, please visit http://www.onsr.tn/

About InstaDeep (https://www.instadeep.com/)

InstaDeep delivers AI-powered decision-making systems for the Enterprise. With expertise in both machine intelligence research and concrete business deployments, we provide a competitive advantage to our customers in an AI-first world. As one of the leading AI companies in Africa, InstaDeep knows first-hand what African talent is truly capable of.

InstaDeep has more than 70 employees spread across its headquarters in London, and offices in Paris, Tunis, Nairobi, and Lagos. In addition to its connections to African educational institutions, the company also possesses strong ties to elite French schools and top-rated universities in the UK.

About AI Hack Tunisia (www.ai-hack-tunisia.com)

The AI Hack Tunisia 2019 is the biggest ML/AI Hackathon ever in Tunisia, Africa, and the Middle East North Africa (MENA) region. It takes place on 20-22 September. The event is a double hackathon: the first part is an individual Machine Learning Challenge, and the second part is a group (or as we like to say, startup) competition focused on a specific technology.

With mentors, judges, and competitors from all over the world, it’s going to be a blast!

The metric used for this challenge is Log Loss.

This metric is used in order to evaluate the error for each number in each license plate. In the test set, we provide 213 images of cars where each image contains only one car and one license plate.

The submission file will have N times 7 rows, where N is the number of images and multiplied by seven because the license plate is composed of two numbers the first one contains at most 3 digits and the second one at most 4 digits. If the first number on the image for example contains only two digits then the first digit should be filled with zero. Also, each row should be one hot encoded. Since we have 10 classes (from 0 to 9) the digit 7 for example should be encoded this way : 0,0,0,0,0,0,0,1,0,0.

Hence, if the two first images contain theses two license plates consecutively:

img_1.jpg

img_2.jpg

Then the submission file should be as follows:

id,    0,1,2,3,4,5,6,7,8,9
img_1_1,0,1,0,0,0,0,0,0,0,0
img_1_2,0,0,0,0,0,0,1,0,0,0
img_1_3,0,0,0,0,0,1,0,0,0,0
img_1_4,1,0,0,0,0,0,0,0,0,0
img_1_5,0,0,0,0,0,0,0,0,1,0
img_1_6,0,0,0,0,0,0,0,0,0,1
img_1_7,0,0,0,0,0,1,0,0,0,0
img_2_1,0,0,0,0,0,0,0,0,0,0
img_2_2,0,0,0,0,0,0,0,1,0,0
img_2_3,0,0,0,0,0,0,0,1,0,0
img_2_4,0,0,0,0,0,0,0,0,0,1
img_2_5,0,0,0,0,0,1,0,0,0,0
img_2_6,0,0,0,0,0,0,0,0,1,0
img_2_7,0,0,0,0,0,0,0,1,0,0

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.

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 only use the data sets provided. External data is not allowed.

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.

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.

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