Application Catalog
The following is a catalog of prebuilt applications designed to accelerate AI development by providing ready-to-use models for well-known tasks. These applications include object detection, depth estimation, semantic segmentation, tracking, and pose estimation.
The catalog is divided into two sections:
Developer Community Applications: Open-source or community-driven AI models for various domains.
SiMa-Provided Applications: Optimized, hardware-accelerated models tailored for SiMa AI processors and multi-camera setups.
These prebuilt applications can significantly reduce development time and provide baseline models that can be fine-tuned for specific use cases.
Developer Community Applications
These applications are developed and contributed by the AI community, covering a wide range of deep learning tasks.
Application Name |
Description |
|---|---|
SingleCameraIndoorsDepth |
Optimized for depth estimation from an image includes Robotics Systems for navigation, object detection, and interaction. |
LeatherAnomalyDetection |
Optimized to identify defects and inconsistencies in leather products ensuring high-quality standards in leather processing, reducing manual inspection efforts and minimizing defects in the final product. |
SafetyHelmetDetection |
Designed for real-time monitoring and detection of safety hazards in various environments such as industrial sites, public spaces, and transportation systems. |
YoloV7 |
Optimized for improved accuracy, speed, and efficiency this application is widely used for AI tasks such as autonomous driving, surveillance, industrial automation, and smart retail. |
SiMa-Provided Applications
These applications are hardware-optimized for SiMa AI accelerators and multi-camera processing, ensuring high performance for edge AI use cases.
Application Name |
Description |
|---|---|
4_cameras |
Multi-camera input processing for real-time applications |
efficient_det |
Efficient object detection model for constrained environments |
open_pose |
Human pose estimation model for activity recognition |
people_tracking |
Real-time tracking of individuals in video feeds |
yolo_v5_ethernet |
YOLOv5 deployment optimized for Ethernet-based processing |
yolo_v5_pcie |
YOLOv5 optimized for PCIe hardware acceleration |
yolo_v7_4_cameras_ethernet |
Multi-camera processing using YOLOv7 over Ethernet |
yolo_v7_ethernet |
YOLOv7 variant optimized for Ethernet communication |
yolo_v7_pcie |
YOLOv7 deployment optimized for PCIe acceleration |