Compare OpenVisionCapsules with TensorFlow, PyTorch, Keras, Caffe, ONNX, etc. formats.
OpenVisionCapsules is a portable NN and algorithm format for TensorFlow, PyTorch, Keras, Caffe, ONNX, etc.—all formats are supported. Through an encapsulation of the other formats and defining a standardized input, output, and configuration, OpenVisionCapsules is a self-contained format and interoperable smart-vision standard. It is designed for both developers and non-developers to use.
- Enable mass production of AI
- Drag-and-drop portable algorithms format to deploy
- Self-contained; downloadable AI, good for both technical developers and non-technical users
- Nearly-instantaneous load or upgrade at run-time
- Tiny footprint
- ~50 lines code: a few hours to learn
OpenVisionCapsules has been contributed to OpenCV.org, adopted as an industry standard for the purpose of:
- Open standard for interoperability across machines, from edge to cloud
- Agnostic to the underneath hardware architectures and machine learning frameworks
- Negligible computing overhead and tiny footprint for embedded systems with limited computing & memory
- Encryption to protect IP of algorithms and Neural network models
Compare neural network model formats with the OpenVisionCapsules format:
OpenVisionCapsules architecture
By encapsulating existing neural network models into OpenVisionCapsules format, you will be able to define the input/output type and pre/post-processing logic. In addition, you can configure the algorithm with a standardized API at runtime. With all the above information encapsulated, the OpenVisionCapsules format becomes completely self-contained. Thus it enables a non-technical person to deploy Neural networks or algorithms without any coding.
Resources
https://github.com/opencv/
OpenVisionCapsules downloads: https://aotu.ai/docs/downloads/
Open-sourced OpenVisionCapsules: https://github.com/aotuai/capsule_zoo.git
OpenVisionCapsules documentation: https://openvisioncapsules.readthedocs.io/en/latest/
OpenVisionCapsules development tutorials: https://aotu.ai/docs/tutorials/capsules/installing_a_capsule/