YOLO Object Detection
Flexible processor for custom YOLO models. Bring your own trained YOLO model and integrate it seamlessly into your application for any object detection task.
View Full DocumentationOverview
The YOLO processor provides a flexible framework for integrating any custom YOLO (You Only Look Once) model into your application. Whether you've trained a model for detecting specific objects, analyzing industrial parts, or identifying custom patterns—this processor handles the integration.
Simply provide your trained YOLO model file, and the processor takes care of inference, result parsing, and optional overlay visualization. This enables rapid deployment of custom object detection solutions without building inference pipelines from scratch.
Key Features & Capabilities
Custom Model Support
Load any trained YOLO model for object detection—from general purpose to highly specialized domain-specific models.
Fast Inference
Optimized YOLO inference pipeline with support for GPU acceleration for real-time object detection performance.
Multi-Object Detection
Detect multiple objects of different classes within a single image with confidence scores and bounding boxes.
Configurable Thresholds
Adjust confidence thresholds and NMS (Non-Maximum Suppression) parameters to fine-tune detection behavior.
Visual Overlays
Automatic visualization of detection results with customizable bounding boxes, labels, and confidence scores.
Flexible Integration
Seamless integration into the CapCognition pipeline with consistent API patterns across all processors.
Common Use Cases
The YOLO processor enables a wide range of object detection scenarios:
Industrial Inspection
Detect defects, parts, or quality issues in manufacturing and production environments with custom-trained models.
Retail Analytics
Identify products, packaging, or inventory items for automated checkout systems and stock management.
Security & Surveillance
Detect specific objects, people, or events in security camera feeds with specialized recognition models.
Scientific Analysis
Recognize patterns, specimens, or features in scientific imagery across various research domains.
Logistics & Transport
Identify packages, containers, or vehicle types in logistics and transportation workflows.
Agriculture
Detect crops, pests, or growth stages for precision agriculture and automated farm monitoring.
Latest Improvements
Highlights from the most recent release of the YOLO Object Detection processor.
Load Any YOLO Model
Bring your own YOLO model trained for any domain and integrate it directly into the CapCognition pipeline for fully custom object detection.
YOLO Formats 5, 8, 26 & 26 e2e
Support for YOLO versions 5, 8, 26, and 26 e2e (end-to-end) covering the most widely used model formats in the YOLO ecosystem.
Local & Runtime Model Loading
Load models from the local file system or download them at runtime from the internet—seamlessly supports both offline and online deployment scenarios.
Model Support
Flexible model loading with support for various YOLO architectures and formats:
Custom Models
Load your own trained YOLO (format: 5, 8, 26, 26 e2e) models in ONNX format for maximum flexibility and compatibility.
Stream Loading
Load models from embedded resources, local files, or network streams with optional encryption support.
Performance Options
Configure inference optimization, model preparation, and caching for optimal runtime performance.