TiVision - Simple Medical Deep Learning Training Annotation Software

TiVision is an all-in-one professional computer vision platform that integrates image annotation, model training, validation prediction, and multi-format model export. The software adopts advanced training algorithms and inference architecture, supports multiple computer vision tasks, and provides a complete workflow solution from data annotation to model deployment. TiVision is committed to providing computer vision practitioners with a professional, efficient, and user-friendly tool platform to promote the application of AI technology across various industries.

​​Multi-functional Annotation Center​

​

​​Multi-type Annotation Support​​: Various annotation tools including rectangle, polygon, circle, ellipse, point, line, etc.

​​Smart Ruler System​​: Integrated precision ruler tool supporting pixel-level accurate positioning and measurement

​​Category Management​​: Flexible category system supporting color customization and batch management

​​Sample Management​​: Intelligent dataset sample management with real-time annotation status display

​Intelligent Training Center​

​

​Multi-task Support​​: Object detection, instance segmentation, pose estimation, image classification, oriented detection, semantic segmentation (under development), panoptic segmentation (under development), multi-task learning (under development)

​​Multiple Model Sizes​​: Nano, small, medium, large, and extra-large model sizes

​​Adaptive Parameter Optimization​​: Automatically recommends optimal parameters based on task type

​​Real-time Monitoring​​: Visualized training process with real-time display of loss curves and accuracy metrics

​​Validation and Prediction Center​

​

​​Model Validation​​: Comprehensive metric evaluation including mAP, confusion matrix, etc.

​​Real-time Prediction​​: Supports single image and batch prediction

​​Result Visualization​​: Overlay display of detection results with adjustable confidence levels

​​Performance Monitoring​​: Real-time monitoring of CPU usage and memory consumption

​​Smart Environment Integration​

​

​​Embedded Python​​: Built-in Python environment, no additional configuration required

​​Offline Deployment​​: Network-independent, completely offline usage

​​Professional User Experience​

​

​​Dual Theme Support​​: Dark/Light themes to reduce visual fatigue

​​Shortcut Key System​​: Customizable shortcut key configuration

​​Multi-language Support​​: Simplified Chinese, Traditional Chinese, English

​​Common Application Fields​

​

​​Industrial Manufacturing​​: Defect detection, product quality control, production line monitoring, etc.

​​Autonomous Driving​​: Traffic sign recognition, pedestrian detection, vehicle recognition, etc.

​​Medical Imaging​​: Lesion detection, cell segmentation, medical image analysis, etc.

​​Retail Industry​​: Product recognition, inventory management, customer behavior analysis, etc.

​​Smart Agriculture​​: Crop monitoring, pest detection, yield estimation, etc.

​​System Requirements​

​

​​Operating System​​: Windows 10/11

​​Memory​​: Minimum 8GB, recommended 16GB or above

​​Storage​​: At least 10GB available space

​​Technical Advantages​

​

​​Integrated Workflow​​: Full-process coverage from data annotation to model deployment

​​High-performance Inference​​: Based on advanced algorithm architecture

​​User-friendly​​: Intuitive interface design lowering the usage threshold

​​High Scalability​​: Modular design supporting functional expansion

​​Note​​: The current version is CPU-only. Training speed remains fast, and training small-sample models completely does not require GPU. With limited resources, we will focus on software feature development. Documentation introduction is subject to actual functions.