# Simuletic - Synthetic Datasets for Computer Vision AI

> Simuletic creates photorealistic synthetic image datasets for training and evaluating computer vision AI models, enabling safe AI development for high-risk and rare-event scenarios without real-world data collection.

## Pages

- [Home](/): Simuletic homepage — synthetic data platform overview and key value propositions.
- [About](/about): Company mission, team, and story behind Simuletic.
- [Platform](/platform): AI synthetic data generation platform capabilities, workflows, and use cases.
- [Solutions](/solutions): Industry-specific synthetic data solutions for security, surveillance, and safety.
- [Use Cases](/use-cases): Real-world AI challenges solved with synthetic training data.
- [Datasets](/datasets): Browse ready-to-use synthetic datasets for computer vision model training.
- [Marketplace](/marketplace): Purchase premium datasets and custom data packages.
- [Pricing](/pricing): Subscription plans, credit packages, and licensing information.
- [Blog](/blog): Articles on synthetic data, AI training, computer vision research, and product updates.
- [Careers](/career): Open positions and working at Simuletic.
- [Open Source](/opensource): Open-source datasets, tools, and community contributions.
- [UAV & Drone Detection](/uav): Synthetic datasets for drone and UAV detection applications.
- [VLM Training](/vlm): Vision Language Model training data and fine-tuning services.
- [Privacy Policy](/privacy): Data privacy practices and GDPR compliance.
- [Terms & Conditions](/terms): Legal terms of service and usage conditions.

## About Simuletic
Simuletic is a technology company that creates photorealistic synthetic image datasets for training and evaluating computer vision AI models. Our solutions enable organizations to safely develop AI for high-risk, sensitive, and rare-event scenarios without collecting real-world data.

## Mission
To accelerate the development of safer AI systems by providing high-quality, privacy-preserving synthetic training data for security, surveillance, and safety applications.

## Core Products & Services

### 1. Ready-to-Use Datasets
Pre-built synthetic datasets with images and YOLO/JSONL annotations for:
- **Pedestrian Attribute Recognition (PAR)**: High-angle CCTV dataset with natural language descriptions and structured attribute maps for Re-ID and VLM fine-tuning (Pedestrian-1K, 10K, 50K)
- **Weapon Detection**: CCTV perspectives with person and weapon class annotations
- **Handgun vs Bag of Chips**: Hard negative mining dataset solving the "Doritos Effect" — reducing false positives where AI confuses snack bags with handguns
- **Rifles vs Umbrellas**: Hard negative mining dataset for reducing false positives in weapon detection (umbrella-like objects)
- **Knife Detection**: Specialized knife detection in security camera footage
- **Fall Detection**: Incident monitoring with bounding boxes and 17-keypoint skeleton annotations
- **Driver Drowsiness**: Eye monitoring for fatigue detection with keypoint annotations
- **Aggressive Pose Detection**: Threatening behavior recognition using pose estimation
- **Drone/UAV Detection**: Military and civilian detection from aerial perspectives
- **Airport Drone Detection**: Rogue drone detection for runway safety and counter-UAS in international airport environments
- **Military Drone Swarm**: Saturation attack benchmarks with tiny object detection
- **Long-Distance Wildfire & Smoke Detection**: Lookout-tower / ridgeline perspective dataset for early-warning wildfire camera networks (smoke + wildfire YOLO classes; 240 open-source / 1,500 full)
- **CCTV ATM Robbery Detection (Gun & Knife)**: High-angle ATM surveillance dataset with role-aware YOLO annotations — offender, victim, gun, knife (240 open-source / 3,000 full)
- **CCTV Shoplifting Detection (YOLO + VLM)**: Retail in-store CCTV dataset with person + 17-keypoint pose + VLM captions + video sequences for temporal action recognition (400 frames + 8 videos open-source / 5,000+ frames + 100+ videos full)

### 2. Weather & Lighting Variations
- Generate nighttime, rainy, foggy, cloudy, and stormy conditions
- Extend existing datasets with realistic weather variations in seconds via API
- Perfect for autonomous vehicles, security systems, industrial monitoring
- Same scene consistency with environmental conditions transformed

### 3. Vision Language Model (VLM) Training
- Custom VLM training data generation
- Pre-trained models for threat detection and scene understanding
- Fine-tuning services for surveillance and security applications

### 4. Custom Dataset Generation
- Bespoke synthetic datasets using customer camera angles and environments
- Tailored scenarios for specific use cases
- No real-world data collection required

### 5. AI Model Evaluation
- Synthetic evaluation imagery from multiple angles
- Performance validation for real-world deployment
- Quality assurance for mission-critical AI systems

## Key Benefits
- **Privacy-Safe**: No real people in training data, GDPR compliant
- **Rare Events**: Generate dangerous or hard-to-capture scenarios safely
- **Precise Labels**: Pixel-perfect annotations impossible with manual labeling
- **Scalable**: Generate thousands of variations from single scenarios
- **Cost-Effective**: Reduce data collection and labeling expenses

## Industries Served
- Public Safety & Security
- Transportation & Automotive
- Healthcare & Elderly Care
- Defense & Military
- Industrial Safety
- Smart Cities

## Technical Specifications
- YOLO format annotations (v5, v8, v11 compatible)
- COCO keypoint format for pose estimation
- JSONL format with natural language descriptions and structured attribute maps
- VLM grounding data for vision-language models
- Evaluation imagery for model testing

## Available Datasets
Browse and download: https://simuletic.com/datasets

Individual dataset pages:
- Pedestrian-1K Attribute Recognition: https://simuletic.com/datasets/pedestrian-attribute-recognition-dataset
- CCTV Weapon Detection: https://simuletic.com/datasets/cctv-weapon-detection-dataset
- CCTV Knife Detection: https://simuletic.com/datasets/cctv-knife-detection-dataset
- CCTV Fall & Incident Detection: https://simuletic.com/datasets/cctv-fall-incident-detection-dataset
- Airport Drone Threat Detection: https://simuletic.com/datasets/airport-drone-threat-safety-dataset
- Aggressive Pose Detection: https://simuletic.com/datasets/cctv-aggressive-pose-detection-dataset
- Rifles vs Umbrellas: https://simuletic.com/datasets/cctv-weapon-detection-rifles-vs-umbrellas
- Handgun vs Chips: https://simuletic.com/datasets/weapon-detection-handgun-vs-chips
- Military Drone Swarm: https://simuletic.com/datasets/military-drone-swarm-saturation-attack-dataset
- Drone Detection (Civilian/Military): https://simuletic.com/datasets/drone-civilian-armed-military-detection-dataset
- Driver Drowsiness Detection: https://simuletic.com/datasets/driver-drowsiness-detection-dataset

## Frequently Asked Questions

### What is synthetic data?
Synthetic data is artificially generated data that mimics the statistical properties and visual characteristics of real-world data. For computer vision, this means creating photorealistic images that can train AI models without using real footage.

### Why use synthetic data instead of real data?
1. **Privacy**: No real people or identifiable information
2. **Rare events**: Generate dangerous scenarios safely (weapons, accidents, threats)
3. **Cost**: Cheaper than capturing and annotating real footage
4. **Annotation quality**: Pixel-perfect ground truth automatically generated
5. **Diversity**: Control lighting, angles, scenarios, and edge cases
6. **Speed**: Generate thousands of samples in hours, not months

### Is synthetic data effective for training AI models?
Yes. Research and industry practice show that synthetic data can significantly improve model performance, especially for rare events. Many models trained on synthetic data transfer well to real-world scenarios, particularly when combined with a small amount of real data for fine-tuning.

### What formats do your datasets support?
- YOLO format (.txt files with normalized bounding boxes)
- COCO format (JSON with keypoints and segmentation)
- Pascal VOC format (XML annotations)
- VLM grounding format (text + bounding box pairs)
- JSONL format (natural language descriptions + structured attributes)

### Can you create custom datasets for my specific use case?
Absolutely. We specialize in creating bespoke synthetic datasets tailored to your camera angles, environments, and specific detection requirements. Contact us at contact@simuletic.com.

## Competitive Positioning

### vs. Real Data Collection
- Simuletic: No privacy concerns, unlimited rare events, instant annotations
- Real data: Privacy regulations, rare events are hard to capture, manual annotation required

### vs. Other Synthetic Data Providers
- Simuletic: Specialized in surveillance/security, CCTV-realistic imagery, defense applications
- Others: Often focused on autonomous driving or general object detection

### vs. Manual Annotation Services
- Simuletic: Perfect ground truth, consistent quality, unlimited scale
- Manual: Human error, inconsistent labels, limited throughput

## Recent Blog Posts
- "How We Document Our AI Systems and Stay Ready for the EU AI Act" (Mar 12, 2026): How Simuletic uses Paracta to classify, document, and govern AI systems under the EU AI Act framework.
- "Your Surveillance AI Deserves Better Data — Introducing Pedestrian-1K" (Mar 3, 2026): Why most PAR datasets are stuck in the past and how synthetic surveillance-first data changes the game.
- "Fixing the 'Doritos Effect': Why AI Mistakes Chip Bags for Handguns" (Feb 14, 2026): Technical breakdown of weapon detection false positives and how hard negative mining with synthetic data fixes it.
- "Synthetic Weather Variations: Complete Your Dataset with Any Condition" (Jan 18, 2026): Generate weather variations for training data via API.
- "When Umbrellas Trigger Lockdowns: Solving False Positives in Weapon Detection AI" (Jan 10, 2026): Hard negative mining for CCTV weapon detection.
- "Airport Drone Detection Dataset" (Dec 28, 2025): Synthetic dataset for runway safety and counter-UAS.
- "Drone Swarm Detection Dataset" (Dec 22, 2025): Counter-UAS saturation attack detection.
- "Synthetic Fall Detection Dataset" (Dec 20, 2025): GDPR-compliant fall detection training data.
- "Synthetic Eyes: Fine-Tuning VLMs for Threat Detection" (Dec 15, 2025): Converting YOLO labels into VLM grounding data.
- "Beyond Blurring: PrivaMasq" (Dec 10, 2025): Real-time synthetic identity replacement for CCTV privacy.

## Legal
- Privacy Policy: https://simuletic.com/privacy
- Terms & Conditions: https://simuletic.com/terms

## Contact Information
- Website: https://simuletic.com
- Email: contact@simuletic.com
- LinkedIn: https://www.linkedin.com/company/simuletic/
- Twitter/X: https://x.com/simuletic

## Related Products
- PrivaMasQ: AI-powered image anonymization using synthetic identity replacement (https://privamasq.com)

## Open Source Samples
Sample datasets available on:
- Kaggle: https://www.kaggle.com/simuletic
- Hugging Face: https://huggingface.co/Simuletic

## Last Updated
March 12, 2026