What is Intel Geti Software?
Intel’s latest software can create computer vision models with less data and in a quarter of the time. Teams can now create unique AI models at scale with to this software, which streamlines time-consuming data labeling, model training, and optimization processes throughout the AI model creation process.
Create Robust AI Models for Computer Vision
Small data sets, active learning, an easy-to-use user interface, and integrated collaboration make training AI models straightforward.
Automate and Digitize Projects More Quickly
Teams can rapidly create vision models for a variety of processes, such as identifying faulty parts in a production line, cutting downtime on the factory floor, automating inventory management, or other digitization and automation projects, by streamlining labor-intensive data upload, labeling, training, model optimization, and retraining tasks. The Intel Geti software simplifies the process and significantly reduces the time-to-value of developing AI models.
Core Capabilities Behind the Next-Generation Computer Vision AI Software
Interactive Model Training
Use as little as 20–30 photos to begin annotating data, and then use active learning to train the model as it learns.
Multiple Computer Vision Tasks
Build models for AI tasks such as anomaly detection, object identification, categorization, and semantic segmentation.
Task Chaining
By chaining two or more tasks together, you may train your model into a multistep, intelligent application without writing extra code.
Smart Annotations
Use professional drawing tools like a pencil, polygon tool, and OpenCV GrabCut to quickly annotate data and segment pictures.
Production-Ready Models
Produce deep learning models as optimized models for the OpenVINO toolkit to operate on Intel architecture CPUs, GPUs, and VPUs, or in TensorFlow or PyTorch formats, if available.
Hyperparameter Optimization
The model’s learning process depends on the hyperparameters being adjusted. The work of a data scientist is made simpler by Intel Geti software’s integrated optimization.
Rotated Bounding Boxes
The accuracy and ease of training are extended to datasets with non-axis-aligned pictures with to support for rotated bounding boxes.
Model Evaluation
Assessment of the Model thorough statistics to evaluate the success of your model.
Flexible Deployment Options to Get You Started
Simply set up your environment and infrastructure and prepare to install Intel Geti software, regardless of whether you want to use your system infrastructure inside your network or benefit from the cloud virtual machine without managing infrastructure.
- On Premise
- Virtual Machine
Enabling Collaboration that Adds Value
In a single instance, cross-functional AI teams work together to examine outcomes instantly. Team members with little to no familiarity with AI may assist in training computer vision models with to the graphical user interface. Drag-and-drop model training is made easy by enabling features like object identification helpers, drawing features, and annotation assistants.
Intel Geti Platform Use Cases
Convolutional neural network models are retrained using the Intel Geti platform for important computer vision applications, such as:
- Semantic and instance segmentation, including counting
- Single-label, multi-label, and hierarchical classification
- Anomaly classification, detection, and segmentation
- Axis-aligned and rotational object detection
Task chaining is also supported, allowing you to create intelligent, multi-step applications.
- Manufacturing: Create AI for industrial controls, worker safety systems, autonomous assembly, and defect detection.
- Smart Agriculture: Create models for self-governing devices that can assess crop health, detect weeds and pests, apply spot fertilizer and treatment, and harvest crops.
- Smart Cities: Create AI-powered traffic-management systems to automatically route traffic, create emergency-recognition and response systems, and utilize video data to enhance safety in real time.
- Retail: Create AI for accurate, touchless checkout, better safety and loss prevention, and self-governing inventory management systems.
- Video Safety: Create task-specific models for the identification of safety gear, PPE, social distancing, and video analytics.
- Medical Care: Create models to help with diagnosis and procedures, assess lab data and count cultures, identify abnormalities in medical pictures, and expedite medical research.
- REST APIs and a software development kit (SDK) may be used to incorporate all of these models into your pipeline, or you can use the OpenVINO toolkit to distribute them.
FAQs
What types of data can Intel Geti handle?
Text, photos, videos, and structured data are just a few of the data kinds that Intel Geti can manage. It excels in processing unstructured data, such as audio and visual inputs for deep learning applications.
