AI Solutions
Software That Can See
We build systems that analyze images and video for detection, inspection and measurement, starting with the data and lighting conditions that decide whether they work.
Overview
Computer Vision Development
Computer vision succeeds or fails on its images. Camera placement, lighting, angle, motion and the variety of real conditions matter as much as the model. Codemotives begins by reviewing sample images or video from your environment and defining what counts as a correct detection, because a model that works on tidy test photos can disappoint on a factory floor or a phone camera.
We handle data collection and labeling guidance, model selection and training, evaluation on unseen conditions, and deployment to cloud services, edge devices or mobile apps depending on latency and connectivity needs. We report precision and recall for each class and discuss which errors cost you most, since missed defects and false alarms rarely carry the same price.
Context
Problems we solve
- 01
Not enough labeled images
Models need varied, accurately labeled examples, including rare defects. Collection and labeling are often the biggest tasks.
- 02
Changing real conditions
Lighting, weather, camera angle and wear change what the model sees, so training data must reflect that.
- 03
Latency and hardware limits
Real-time use on edge devices restricts model size and speed. Trade-offs need testing early.
- 04
Privacy of people in images
Cameras that capture faces or workplaces raise privacy and consent questions that must be designed for.
Capabilities
What we deliver
- 01
Image data strategy
Guidance on capture setup, sampling, labeling standards and tooling for building a usable dataset.
- 02
Detection and classification
Models that find, count, classify or segment objects in images and video.
- 03
Visual inspection
Defect and quality checks on products or surfaces, tuned to your tolerance for missed and false alerts.
- 04
Edge and mobile deployment
Optimized models running on cameras, embedded boards or phones when cloud round-trips are not practical.
- 05
Evaluation by class
Precision, recall and confusion analysis on held-out images from varied conditions.
- 06
Review and retraining loop
Interfaces for correcting results and feeding hard cases back into training.
Where it fits
- Defect detection on a production line
- Counting stock or items from shelf photos
- Reading meters and labels from camera images
- Safety equipment checks on site cameras
- Image-based product search in an app
Technologies we use
- Python
- PyTorch
- OpenCV
- YOLO
- TensorFlow Lite
- ONNX Runtime
- NVIDIA Jetson
- CVAT
Approach
How we deliver
- 1
Discover
We learn your goals, users, constraints and existing systems before proposing anything.
- 2
Plan
Scope, priorities, architecture and milestones are agreed so everyone knows what ships when.
- 3
Design
User flows, interfaces and technical design are shaped and reviewed with you early.
- 4
Build
Work is delivered in short iterations with regular demos, so progress is always visible.
- 5
Test
Functional, integration and performance checks run throughout, not only at the end.
- 6
Launch & support
We deploy, monitor and keep improving the product after it goes live.
FAQs
Common questions
Have a question that is not covered here? Get in touch.
How many images do we need?
It varies with task difficulty and the variety of conditions. Pretrained models reduce the amount needed, but representative and correctly labeled examples remain the foundation. We assess a sample before estimating.
Can it run without an internet connection?
Yes, models can be optimized to run on-device or on local hardware. This trades some accuracy or flexibility for speed, privacy and independence from connectivity.
Do you do facial recognition?
We are cautious about it because of legal, ethical and accuracy concerns that vary by region. If your use case involves identifying people, we would discuss the legal context and alternatives before proposing anything.
Let's build what's next
Tell us about your idea, product or legacy system. Send us a message and we will help you scope the right next step.