live-demo

Real-time pose estimation accelerated with NVIDIA TensorRT

Simple python WebUI for fine-tuning ChatGPT (gpt-3.5-turbo)

Create a smart video application using the Intel Distribution of OpenVINO toolkit. The toolkit uses models and inference to run single-class object detection.

Use computer vision inference in the Intel® Distribution of OpenVINO™ toolkit to provide analytics on customer engagement, store traffic, and shelf inventory.

Create a smart video application using the Intel Distribution of OpenVINO toolkit. The toolkit uses models and inference to run single-class object detection.

🌎 Live Demo with ⚡ PowerGrid examples

Observe workers as they pass in front of a camera to determine if they have adequate safety protection.

Natural language for repeating dates

Create a concurrent video analysis pipeline featuring multistream face and human pose detection, vehicle attribute detection, and the ability to encode multiple videos to local storage in a single stream.

Build a solution to analyze customer expressions and reactions to product advertising collateral that is positioned on retail shelves.

Predict performance issues with manufacturing equipment motors. Perform local or cloud analytics of the issues found, and then display the data on a user interface to determine when failures might arise.

Monitor mechanical bolts as they move down a conveyor belt. When a bolt of an irregular size is detected, this solution emits an alert.

Monitor three different streams of video that count people inside and outside of a facility. This application also counts product inventory.

Secure work areas and send alerts if someone enters the restricted space.

Receive or post information on available parking spaces by tracking how many vehicles enter and exit a parking lot.

Run multiple independent anomaly detection (object flaws and motor defects) workloads on a single system via multiple virtual machines using a Kernel-based Virtual Machine (KVM) host.

Detect various irregularities of a product as it moves along a conveyor belt.

Elara enables creating a Windows/MacOS like window manager experience inside a web browser. This JavaScript library is written with performances and compatibility in mind. No third-party libraries or frameworks are needed to use Elara. Open the live demo to try it yourself.

Use a visual heat or motion map to count the number of people that enter and exit a store, factory, or warehouse aisle.

Detect various irregularities of a product as it moves along a conveyor belt.