Road Segment Identification Hackathon by #ZindiWeekendz
Can you identify which images have a segment of a road in them or not?
$300 USD
Ended ~1 year ago
70 active ยท 138 enrolled
Good for beginners
Computer Vision

Governments around the world spend resources mapping roads in their countries to make sure that resources, such as emergency services and education, can reach as many people as possible. Many roads are constructed by the government, but many are created by people trying to reach a new location or creating a shortcut. New roads often pop up around development sectors such as mines and farms. In these cases, government officials need to physically confirm the presence of the road, measure and map the road, and ensure that it is usable.

The objective of this competition is to identify whether an image contains a road segment or not. Dry river beds, railway tracks and power lines could look like roads. It is important to classify these as “not roads”.

This will allow government officials to focus on areas they might need to send an official to confirm the road placement, and add it to the government’s maps and road networks. This is a small part of a larger project to fill in missing roads (i.e a more complete roads network), and also make sure that any current road network is properly joined (node to node), making network analysis easier.

About SDG9: Innovation and Infrastructure

Aging, degraded or non-existent infrastructure makes conducting good business challenging. Business relies on materials, resources, labor and service support from all corners of the world and the ability to access them efficiently is key to establishing new markets. Computing and technology-based skills are of significant value to most businesses today, and consumers of common goods and services live on every continent. However, basic infrastructure supporting technologies, communications, transportation, and sanitation that business relies on is not universally available, hindering economic growth and societal progress.

This presents an opportunity for business. By committing to sustainable industrialization and promoting innovation across company operations, businesses can contribute to development efforts in the regions in which they operate through upgrading local infrastructure, investing in resilient energy and communications technologies, and making these technologies available to all people, including marginalized groups, who might not have access otherwise. Global companies can also promote inclusive infrastructure development by bringing valuable financial services and employment opportunities to smaller and/or minority-owned businesses.


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.


The evaluation metric for this competition is Area Under the Curve (AUC).

For every row in the dataset, submission files should contain 2 columns: ID and Target.

Where 1 indicates that the image contains a road and 0 indicate that the image does not contain a road.

Your submission file should look like this (numbers to show format only):

Image_ID       Target   
ID_D9ONL553    0.13   
ID_263YTILY    0.87

1st Place: $150 USD

2nd Place: $100 USD

3rd Place: $50 USD


Competition closes on 5 September 2021.

Final submissions must be received by 11:59 PM GMT.

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