quailrobot/thermal-v4-sample

QM Synthetic Thermal Airspace: Drone vs Bird (LWIR) - Free Sample

Buy the full commercial edition: $24 USD - launch price until 24 Oct 2026 (regular price $39 USD) -> Polar checkout, instant download Also on Gumroad.
This free sample is non-commercial (CC BY-NC-SA 4.0). The paid full edition has a commercial licence.

Custom dataset of YOUR object ($249)

Need data of YOUR object? Custom synthetic dataset, $249 USD -> order on Polar

• What you get: 2,000 labelled photoreal synthetic images (640x640 JPEG) of your own object or scenario (product, part, tool, drone, package, defect...), up to 3 classes, YOLO bounding boxes + data.yaml, train/val/test split, quality report
• Licence: commercial use allowed
• Price: $249 USD one-time; one round of adjustments included
• Delivery: typically 3-5 business days after we receive your reference photos + rough dimensions
• Optional sim-to-real test: send ~200 of your own labelled real images and we report how much the synthetic data improves a detector on them
• Refund: full refund if we cannot deliver your request (14-day refund policy)
• Limits: only objects you own or are allowed to use; no weapons or anything meant to harm people; no copied third-party 3D assets
• Order URL: https://buy.polar.sh/polar_cl_AQu6LzRtqiQmKPlgPt0zePBtvWjJI4vULeFMQ4NLHH9
• Details + contact: https://quailrobot-quailmodel.static.hf.space

Summary

Synthetic thermal (LWIR-style) images of drones, fixed-wing UAVs and birds with YOLO bounding boxes, for training drone-vs-bird object detectors; the paid full edition can be used commercially.

• Best for: pre-training or augmenting thermal drone/bird detectors, counter-UAS research prototypes
• Not for: claims of real-world detection performance without your own real-footage test

Quick start

# pip install huggingface_hub ultralytics
from huggingface_hub import snapshot_download
path = snapshot_download("quailrobot/thermal-v4-sample", repo_type="dataset")
from ultralytics import YOLO
YOLO("yolov8n.pt").train(data=f"{path}/data.yaml", epochs=50, imgsz=640)

Facts

• Task: object detection (YOLO format)
• Labels: 3 classes: 0 multirotor, 1 fixed_wing, 2 bird; empty label file = true negative
• Full edition size: 5,000 images 640x640 (train 4,029 / val 490 / test 481) with YOLO labels (zip 517.7 MB)
• Free sample size: 300 images (train 242 / val 27 / test 31)
• Format: JPEG images + YOLO txt labels + data.yaml (Ultralytics-ready)
• What's included (full edition): images/{train,val,test}, labels/{train,val,test}, data.yaml, README.md, LICENSE.txt
• Price: $24 USD, launch price until 24 Oct 2026 (regular price $39 USD); checkout may display the equivalent in your local currency
• Buy URL (primary): https://buy.polar.sh/polar_cl_rkadu8XB0RMWuFbrE1ww9wAdP1wJsOSEz5qz73P2B2g
• Buy URL (secondary, also on Gumroad): https://quailcraft1.gumroad.com/l/synthetic-thermal-airspace-drone-bird
• Licence (full edition): LicenseRef-QuailModel-Commercial (commercial use allowed, no resale of the data)
• Licence (free sample): CC-BY-NC-SA-4.0
• Validation: Labels are computed from exact projected 3D mesh vertices with ray-cast occlusion checks (objects under 8 px dropped). No benchmark on real thermal footage has been published for this edition yet.
• Data source: 100% synthetic, generated by QuailModel with AI assistance (generator code written with an AI model)
• Catalog (all QuailModel datasets, catalog.json, llms.txt): https://quailrobot-quailmodel.static.hf.space
• Last updated: 2026-10-10

Validation

Labels are computed from exact projected 3D mesh vertices with ray-cast occlusion checks (objects under 8 px dropped). No benchmark on real thermal footage has been published for this edition yet.

Price & licence

• Full edition: $24 USD, launch price until 24 Oct 2026 (regular price $39 USD). One-time payment, instant download after checkout: https://buy.polar.sh/polar_cl_rkadu8XB0RMWuFbrE1ww9wAdP1wJsOSEz5qz73P2B2g (also on Gumroad: https://quailcraft1.gumroad.com/l/synthetic-thermal-airspace-drone-bird)
• QuailModel Commercial Dataset Licence (SPDX: LicenseRef-QuailModel-Commercial): you may train, evaluate and ship models, including in commercial products. You may not resell or redistribute the dataset itself.
• Free sample (this page): CC BY-NC-SA 4.0 - free for non-commercial use.

Limitations

• 100% synthetic, procedurally rendered: validate on real thermal footage before deployment.
• 22% of boxes are smaller than 16 px (small-target detection is hard by design).

This free sample: 300 images (train 242 / val 27 / test 31). Full commercial edition: 5,000 images 640x640 (train 4,029 / val 490 / test 481) with YOLO labels (zip 517.7 MB). Fully synthetic data; summary, facts, validation and limitations are in the block above.

Contents

split	images	boxes
train	242	402
val	27	34
test	31	45

• Image size: 640x640 JPEG. Labels: YOLO txt, classes: 0 = multirotor, 1 = fixed_wing, 2 = bird. Images with an empty label file are true negatives (44 of 300).
• Boxes per class: multirotor 266, fixed_wing 119, bird 96
• data.yaml included - train directly with Ultralytics YOLO.
• Box size distribution (fraction of image width): median 0.066, 22% of boxes are smaller than 16 px.

How it was made

Original 3D models, procedurally generated and rendered with a physically based renderer under real-world lighting, with realistic camera effects. Labels are computed exactly from the 3D scene (no hand labelling).

Credits

Lighting environments: Poly Haven HDRIs (CC0), credited.

Licence

Sample edition: CC BY-NC-SA 4.0 (non-commercial). The full commercial edition is sold by QuailModel (see the buy link).

Disclosure

Generated by QuailModel with AI assistance (generator code written with an AI model); all data is synthetic / computer-generated. Validate on your own real data before production use.