Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Deploying CV/NLP with CANN
- The AI model lifecycle, from initial training to final deployment
- Critical performance factors for real-time CV and NLP applications
- An overview of CANN SDK tools and their function in model integration
Preparing CV and NLP Models
- Exporting models from PyTorch, TensorFlow, and MindSpore
- Managing model inputs and outputs for image and text tasks
- Utilizing ATC to transform models into OM format
Deploying Inference Pipelines with AscendCL
- Executing CV/NLP inference via the AscendCL API
- Preprocessing workflows: image resizing, tokenization, and normalization
- Postprocessing steps: handling bounding boxes, classification scores, and text output
Performance Optimization Strategies
- Profiling CV and NLP models using CANN tools
- Minimizing latency through mixed-precision and batch tuning techniques
- Optimizing memory and compute resources for streaming tasks
Computer Vision Use Cases
- Case study: object detection for smart surveillance systems
- Case study: visual quality inspection in manufacturing environments
- Creating live video analytics pipelines on Ascend 310
NLP Use Cases
- Case study: sentiment analysis and intent detection
- Case study: document classification and summarization
- Real-time NLP integration via REST APIs and messaging systems
Conclusion and Future Steps
Requirements
- Proficiency in deep learning concepts for computer vision or NLP
- Practical experience with Python and AI frameworks like TensorFlow, PyTorch, or MindSpore
- A fundamental grasp of model deployment or inference workflows
Target Audience
- Computer vision and NLP professionals utilizing Huawei’s Ascend platform
- Data scientists and AI engineers building real-time perception models
- Developers integrating CANN pipelines within manufacturing, surveillance, or media analytics contexts
