alwaysAI fast-tracks the creation and deployment of computer vision apps on edge devices. Our developer platform works with many AI model framework technologies and endpoint environments, and comes pre-loaded with a growing model catalog, starter apps, and core computer vision functionalities (including object detection, tracking and counting; image classification, pose estimation, and semantic segmentation) enabling the development of a wide range of computer vision applications.
With the advent of artificial intelligence technologies and increasing sophistication of computer vision platforms like alwaysAI, we want to see projects that incorporate this technology to improve the world we live in. We want to see computer vision being used for social good, or a sustainability project.
How would you make an impact to the world, if you could give intelligent sight to a machine?
Examples:
**WINNING TEAM RECEIVES A Robot Kit **
Winning Criteria
Project must use the alwaysAI platform
Additionally, each team will be judged and rated 1-5 points or each of the following:
Prize Details
Ready to create a computer vision application for an edge device? Get started below.
Our easy-to-use platform brings together model frameworks, APIs and embedded environments in just three steps:
Select from a catalog of deep learning CV models or upload your own.
Use our flexible and customizable APIs to quickly enable core computer vision services.
Quickly prototype, test and iterate with a variety of camera-enabled ARM-32, ARM-64 and x86 devices.
Install alwaysAI tooling
Select model based on computer vision project
Use edgeIQ APIs to build your application
Deploy to edge device via Docker image
Run application on the edge device
TensorFlow
Caffe
Darknet (YOLO)
Object Detection
Image Classification
Object Tracking
Object Counting
Facial Detection
Human Pose Estimation
Semantic Segmentation
Prediction Labels
Prediction Confidences
Prediction Filtering
Image Manipulation
Video Manipulation
Docker on ARM32
Docker on ARM64
Docker on x86
Qualcomm Snapdragon
Qualcomm RB3
NVIDIA Jetson
Intel Myriad Accelerator