# Computer vision development company

> Object detection, image classification and video analysis for real business problems. Custom computer vision tested on your images. Book a free 30-minute call.

Source: https://codeintelli.com/services/computer-vision-development

Someone still checks every image by eye. A camera can do the first pass.

We build computer vision systems that spot defects, count stock, read labels and flag safety issues, running in the cloud or on devices at the edge.

## Problems we solve

- Our inspectors miss things late in a shift: Manual checks get slower and less accurate as the day goes on.
- We record hours of video that nobody watches: The footage is there after something goes wrong, never before.
- The off-the-shelf model doesn't know our products: Generic vision APIs can't tell your good part from a bad one.
- It worked in the lab, not on the floor: Lighting, angles and dust broke the model the week it went live.

## What we build

- Defect and quality inspection: Spot scratches, missing parts and assembly errors on the line
- Object detection and counting: Count stock, people or vehicles and track them across frames
- Text and label reading: Read labels, serial numbers, plates and documents from images
- Edge deployment: Fast, private processing on local devices with TensorRT and ONNX

## How we work

- Assess (1-2 weeks): We review your cameras, lighting, sample images and the decision you need. We tell you what accuracy is realistic before we build.
- Collect (2-4 weeks): We set up image capture and labelling in tools like Label Studio, working with your experts on what counts as a defect or a match.
- Build (8-14 weeks): We train and test the model, then deploy it to the cloud or edge devices with a screen your team uses to review results.
- Monitor (Ongoing): We track accuracy on live images, collect the hard cases and retrain on a schedule you agree.

## Results

- Example: Defect detection: For example, for a factory we would build a camera check that flags faulty items on the line and logs each one.
- Example: Shelf monitoring: For example, for a retailer we would build a camera system that spots empty or messy shelves and alerts staff.
- Example: Parcel label reading: For example, for a warehouse we would build a scanner that reads labels from photos and fills in the record.

## Technologies

PyTorch, TensorFlow, YOLO, Detectron2, OpenCV, NVIDIA TensorRT, Edge AI, AWS Rekognition, Google Vision, Azure CV, Custom CNNs, ViT models, ONNX, Label Studio

## Questions

### How accurate will it be?
That depends on your images, and we won't guess. In the assess phase we test on your real samples and tell you what's realistic. Most clients start with the system flagging items for a person to confirm.

### We don't have labelled images. Can we still start?
Yes. Collecting and labelling data is part of the work. We set up the process, label alongside your experts and hand you the dataset as your own asset.

### Can it run without sending video to the cloud?
Yes. We can run models on edge devices or local servers, so images stay on site. We'll recommend the setup that fits your speed, cost and privacy needs.

### What will it cost, and how do we track progress?
You get a written plan and a fixed price within 48 hours of our call. Then you see working results in a demo every week, and we flag early if anything will take longer or cost more.

## Contact

- Email: biz@codeintelli.com
- Phone / WhatsApp: +91 92745 85376
- Book a free 30-minute call: https://codeintelli.com/book-a-call