Home / Services / Object Detection Development
Computer Vision / ML / DL
Object detection systems for images and live video
Object detection finds and labels specific things in an image or video frame: a missing hard hat, a damaged part, a vehicle, a product on a shelf. We train detectors on your own images so they work in your conditions, not only on a demo dataset.
What we build
Object Detection Development: what you get
- Custom detectors trained on your own objects and camera views
- Dataset collection plan, labelling guidelines and quality checks
- Evaluation on held-out images from your real site, explained in plain terms
- Bounding boxes, counts and alerts delivered to your app or dashboard
- Real-time pipelines for live camera streams
- Retraining routines so the model improves as new cases appear
This is a good fit if…
- You need to count, locate or flag specific objects automatically
- Generic models miss your objects or conditions
- Reviewing images or footage by eye takes too long
Typical uses
- Detect missing safety equipment in site photos
- Count products on a conveyor or shelf
- Spot damaged parts before packing
How it works
A simple process, no surprises
- 1
Discovery
We collect sample images from your real cameras and list the objects to find.
- 2
Scope and plan
We agree how to label them and what precision and recall you need.
- 3
Build and review
We train, test on held-out images from your site, and review the errors with you.
- 4
Deliver and support
We deploy the detector, document how to retrain it, and monitor results after launch.
Technologies we use for this
- YOLO
- PyTorch
- OpenCV
- ONNX / TensorRT
- Labelling tools (CVAT)
- Python
Reviews
What clients say
★★★★★
“They took a task my team repeated every week and turned it into a single button. Clear communication throughout, and the handover documentation meant we could use it straight away”
FAQ
Object Detection Development: common questions
How many images are needed to train a detector?+−
It depends on how many object types there are and how varied the scenes are. A few hundred well-chosen images can be enough for a narrow task; varied sites need more. We assess this during discovery and tell you honestly.
What about objects that are small or partly hidden?+−
Small and partly hidden objects are harder. Camera position, resolution and lighting matter as much as the model, so we review these first and test on your own footage.
Can it run in real time?+−
Yes for most tasks, on a suitable GPU or edge device. We confirm speed on your hardware before committing.
Can new object types be added later?+−
Yes. Labelling and training are repeatable, so new classes can be added with fresh examples.
Related services
Need object detection development?
Show us the objects you need found and a few sample images. We will tell you how we would approach it.
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