Help Chip solve problems using Anomalib and OpenVINO™! Upskill your AI techniques, show off to friends, and create a solution for a chance to win cool prizes.
Help Chip find all the bad produce at his farm-to-table business using anomaly detection by sharing your knowledge, running a Jupyter notebook or creating an app with OpenVINO.
Choose one or more of the tasks below for a chance to win!
Prepare to detect bad produce by completing some training! Learn about anomaly detection from Chip, then answer a few questions on the form below for a chance to win a Chip's Challenge T-shirt. Try out another task below for a chance at more prizes!
Anomaly Detected
SUBMISSIONS CLOSED
Play
Quick Start with Anomaly Detection!
Get a chance to win an Arc GPU by completing the steps below:
Run our getting started Jupyter notebook and submit a screenshot showing the result from your anomaly detection. Use a different object than a bottle.
Get started easily by running our Jupyter Notebook.
SUBMISSIONS CLOSED
Feeling confident with anomaly detection? Create an app with Anomalib & OpenVINO in the task below for a chance to win a NUC!
Build
Create with Anomalib and OpenVINO!
Anomaly Detected
Download Anomalib and use our OpenVINO notebook as inspiration to build an anamoly detection app showcasing a real-world solution. Start from scratch or add Anomalib to one of your existing apps, then submit your solution for a chance at the Grand Prize, a NUC! Get even more inspiration from our defect detection kit.
Check out Anomaly detection models supported by OpenVINO:
If you need additional support chat with Intel's support team in our repo.
OpenVINO is the toolkit and inference engine that enables segmentation to work on your hardware with enhanced performance and efficiency. You can also include OpenVINO optimization and inference in your pipeline.
SUBMISSIONS CLOSED
Chip's Community Gallery
Spotlighting the latest anomaly detection solutions.
Thank you for all who participated in the Precise Segmentation challenge this past fall. Submissions are now closed, but we encourage you to try out the challenge below and share your submissions on LinkedIn using #chipschallenge to show us what you built!
Whereas object detection identifies the local area of an object to draw a bounding box around, segmentation categorizes every pixel into its own class. This enables more granular image regions.
Help Chip prepare for our hands-on segmentation tasks by completing some diagnostics first! Answer a few questions on the form below for a chance to win a Chip's Challenge T-shirt, then run a segmentation notebook or create an app with OpenVINO for a chance at more prizes.
Run our example notebooks below! Prebuilt components and code lets you quickly see segmentation in action. For example, Segment Anything Model (SAM) is a popular way to “cut out” anything from an image.
Get segmentation up and running!
Get a chance to win an Arc GPU by completing the steps below:
Feeling good about what you've learned so far? Create an app with OpenVINO in the task below for a chance to win a NUC!
Create with OpenVINO!
Download OpenVINO and use our notebooks as inspiration to build a segmentation app showcasing a real-world solution. Start from scratch or add OpenVINO to one of your existing apps, then submit your solution for a chance at the Grand Prize, a NUC!
But why use OpenVINO?
OpenVINO is the toolkit and inference engine that enables segmentation to work on your hardware with enhanced performance and efficiency.
Thank you for all who participated in the Detect Faster challenge this past summer. Submissions are now closed, but we encourage you to try out the challenge below and share your submissions on LinkedIn using #chipschallenge to show us what you built!
Chip has met a friend who needs help detecting objects. Help Chip tap into Ultralytics YOLOv8 and OpenVINO to detect faster. Choose your skill level below to complete the challenge.
Everyone is eligible to complete activities and learn about OpenVINO. However, you are only eligible to win or be awarded prizes if:
You are at least 18 years of age.
You are not a resident of Cuba, Iran, North Korea, Sudan, or Syria due to US export regulations that prohibit the export of goods and services to these countries. Due to a temporary logistics suspension from our shipping carriers, we are not able to ship prizes to participants in Russia, Belarus, or Ukraine.
You are not involved in the execution or administration of Chip's Challenge.
You are not an employee of, or immediate family member or household member of, a Hackster, Intel or Avnet employee.
There is a limit of one (1) entry per person for task 1, "Learn: Show off your knowledge" and three (3) entries per person for task 2 "Play: Quick Start with Anomaly Detection" and task 3 "Build: Create with Anomalib and OpenVINO" of the Anomaly Detection challenge.
What are the prizes for the anomaly detection challenge?
The prize for task 1, "Learn: Show off your knowledge" is a limited edition Chip's Challenge T-shirt.
The prize for task 2, "Play: Quick Start with Anomaly Detection" is an Acer Predator BiFrost Arc A770 GPU.
The prize for task 3, "Build Create with Anomalib and OpenVINO" is the grand prize of a NUC 12 Enthusiast Mini PC.
Does everyone win a prize?
No, there are a limited number of prizes for each challenge. Submitting an entry does not guarantee you will win a prize.
How are winners announced?
Winners will be contacted via the email used when submitting their entry in the challenge.
I won a prize! When will I receive it?
The prize fulfillment process will take up to 8 weeks after winners have been announced. You will receive an email when your prize has shipped. If you need to make any changes to your address during that time, please contact us at events@hackster.io.
2. Identify a real-world problem that could be solved with object detection.
3. Solve it by creating an object detection application. Use pretrained or custom models and make sure to optimize them with OpenVINO. Be creative - the possibilities are endless.
4. Take a screenshot of your notebook and of your object detection and share your results on LinkedIn with #chipschallenge.
What is Anomaly Detection?
Anomaly detection identifies defects in real time through computer vision. It’s useful for quality control in manufacturing, healthcare, agriculture, and more. In real world situations, there are many rare or unknown defects that can occur, which cannot be handled by supervised learning. Anomalib is an open source library that enables unsupervised anomaly detection.
