Start Developing for Computer Vision

Explore tailor-made Learning Paths on Hugging Face.

Learn More

Learn the architecture, neural networks, and tool choices for Grovery's AI-powered trail camera.

Read Case Study

Learning Paths

Learning paths are created by Arm and the Arm software developer community to solve problems developers face while developing on and for Arm.

slide 1 to 4 of 7

Use MediaPipe’s Multimodal AI, Kotlin Flows, and CameraX.

Learn to profile an Android example using LiteRt.

Explore ML apps to evaluate software and performance on Cortex-M55, Ethos-U85.

Run an application on an embedded device from Himax.

Learn efficient on-device LLM inference with lama, KleidiAI, ExecuTorch, and XNNPACK.

Apply deep learning to OCR text recognition.

Benchmark ML workloads on Arm servers using TensorFlow and MLPerf.

Learn the basics of building a computer vision application on Android using OpenCV.

slide 1 to 3 of 3

This blog showcases Ethos-U55 performance with two TinyML apps on a microcontroller.

How Arm powers smart, energy-efficient ML edge devices for developers and IoT.

See what's new in KleidiCV 0.2.0 and 0.3.0: Multithreading, OpenCV 4.11, and performance upgrades.