Learning Wizard
Overview
This document provides guidance for the development of deep neural network (DNN) apps from existing models through the use of Python APIs provided by the Python Ascend Computing Language (pyACL), for such purposes as target recognition and image classification.
With this document, you will be able to:
- Describe the pyACL architecture, basic terms, and typical API call sequences.
- Describe the procedure and implementation of app development using pyACL APIs.
- Develop additional apps based on the provided samples.
To better understand this document, you are supposed to have:
- Proficiency in Python development.
- Knowledge of machine learning and deep learning.
Document Usage Suggestions
If you are using this document for the first time or are not clear about the following problems, learn about the overall application development process from Getting Started and Overview, and then learn about the API calling processes and sample code from sections Runtime Management, DVPP Image/Video Processing (Media Data Processing), and Single-Operator Calling.
- Where is pyACL in the overall architecture?
- What are the functions of the devices, streams, and contexts in pyACL?
- What is the basic workflow for developing apps using pyACL APIs?
If you want to dive deeper, refer to the following app development wizard.
