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Computer Vision Development Services  

Computer Vision Development Services

Machine Vision Solutions Built From Scratch and Tailored to Your Needs

Computer Vision (CV) has evolved from a relatively simple and open-source field in its early days to a highly competitive and closely guarded technology. Technological advances have led to rapid growth in the field, allowing for more advanced solutions that can’t be found open source or out-of-the-box. That’s why at DAC.digital, you’ll find experts and technologists who will create a solution tailored to your needs cross-framework, especially if it means researching and building it from scratch.

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Computer Vision Case Studies

Our experience in AI and computer vision technology ranges from relatively technology-simple image classification through object tracking to complex 3D object estimation based on the point cloud.

Remember that the experience and technology used in these projects are easier to transfer between industries than you might think. So, if a project has inspired you, let us know, and we can work together to see how best to implement it in your organization.

Nail Detection Computer Vision and Deep Learning Models and Algorithms Helped Build a Fully Automated Manicure Robot

  • Our beauty technology startup client entrusted us with building a vision system for precise nail detection for a manicure robot.
  • The robot uses machine-learning algorithms we created to interpret the images from five cameras and precisely detect the position of the hand and nails inside for precise manicure application.
  • By combining different methodologies and challenging the state-of-the-art, our engineers built a complete model that can detect the hand’s position in the 3D space and precisely identify the surface of a nail with an accuracy of under 0.25mm.

Gaze Estimation Project that Disrupts Market Research By Tracking User’s Eye Movements On a Phone Screen

  • Our client’s project involved using a smartphone’s front camera to track the user’s eye movements on the screen and what catches their attention.
  • We used our computer vision and artificial intelligence expertise to research a machine-learning model that detects the user’s face and then “gaze points”—the points at which the user’s gaze stops on the screen and for how long.
  • Since the model has to work in a dynamic environment that cannot be controlled, we used a vast amount of data on people using their smartphones to train it.
  • Since the project breaks state-of-the-art standards, we’re continuously working on increasing the accuracy of eye-tracking efforts.

Ball Trajectory-Tracking App Allows Football Enthusiasts to Improve their Shots on Goal with as Little as a Smartphone

  • We built a ball trajectory-tracking application with a computer vision detection and tracking module for a sports tech startup.
  • Our experts created a complete detection model that, after calibration, precisely tracks the trajectory and speed while shooting on goal.
  • The application and computer vision component use only the phone’s rear camera, making it accessible to almost anyone.
  • Accurate performance allows the users to improve their scoring technique in all conditions.
Computer Vision Detection and Tracking Solutions

Bring us your vision, and we’ll give you the solution.

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Computer Vision Solutions    

From research, data collection and preparation through PoC, MVP and solution scaling for your growing needs, you can rely on us to build a complete product.

Computer Vision R&D Helps You Find Technologies Most Suitable for Your Needs    

There are many ways to build a computer vision algorithm for your solution. Our experts can help you select open-source and customised options for your business needs. However, in some cases, it is best to research and build a vision solution from scratch. This choice should be a conscious decision based on business and technology situations and goals. We can help you explore, understand, and build a project roadmap. Our expert engineers and scientists will help you make the best decision.

Computer Vision Engineer Team

Your Computer Vision Solution Can Only Be as Good as the Data You Base It On. No Data? No Problem

Artificial intelligence-based solutions rely heavily on quality data for training, and CV is no exception. You can find yourself at different data collection stages. You might already be prepared with quality data, require annotation to visual input or still need to collect it. Whatever your situation, you can rely on us to build a solid database, annotate it, establish the ground truth, and extract the most from it to create a viable solution.
Computer Vision Solutions and Services

1. You’ve Got an Idea for a Product or Outcome but Have No Data

You have an excellent idea of using computer vision technology to enhance your business, but you haven’t collected any data yet. That’s no problem. We will collect the data from licensed sets suitable for commercial use or via outsourcing. It will be enough to help train the algorithm for reliable performance.

A drone with a camera can help a farmer with monitoring crop growth. Deep learning-based detectors can analyse video data, raise alerts on possible losses, and calculate the waste percentage. Automated monitoring systems can help increase security by automatically detecting intruders or thieves.

2. You’ve Got Visual Input that Lacks Annotation

Correct image annotation is essential for building reliable machine and deep-learning models. Annotation is a process of labelling images using text, dedicated tools or both. It allows us to draw out and highlight the features the model should learn to recognise autonomously. If you need annotation for your visual data, our team will deliver it and help you create a complete, quality database.

3. You’ve Got Complete, Quality Data and Are Ready to Make the Most of It

Ideally, you already have high-quality annotated data to feed into a machine-learning model. In this case, you can use our expertise to get the most out of your computer vision solution by optimising the datasets or perhaps even suggesting additional ways in which the solution can help your business.

Inspecting harvests can help detect diseases affecting crops and help find a solution to counteract them. Image-supported sorting stands can save manual labour by visually inspecting and automatically separating flawed plants.

Computer Vision Dataset
Computer Vision Image Annotation
Computer Vision Image Analysis

Computer Vision Solution Scaling Is the Real Challenge that You Will Overcome with Us

AI is a relatively new technology constantly developing, and your product will require updates, improvement, and maintenance to bring you maximum value. Processing large quantities of high-resolution data and hardware limitations are the most common scaling challenges. It’s a territory with many variables, a wide range of data, and edge cases for which the solution must be prepared.

Cloud computing is an optimal solution for scaleable data management and can also help in cases of hardware constraints alongside specialised hardware like GPUs and TPUs.

Creating repeatable, automated workflows and ML pipelines ensures swift adaptation to growing business needs without significant disruptions. Edge computing allows for data analysis at the point of its origin, addressing latency issues. You can rely on our expertise to help you choose the right solutions for your scalability needs.

Let’s use a practical example to illustrate the difference between building and scaling.

An Example: Queue Length Monitoring in a Hotel Chain

Let’s imagine you own a chain of 100 5-star hotels. You want your customers to experience the best service possible, so you test this idea on just one hotel. The goal is to automate the reception queue monitoring through CV-enhanced analysis of images from cameras in the lobby. 

You set up a proof of concept, and it works great. So, you decide to apply the solution to the other hotels in your chain. But soon, you will most likely find out it’s not as effective as expected.

Building and implementing a CV solution on a large scale are two sets of challenges. The model trained for the first hotel is not ready for the specific conditions of each hotel lobby in your chain. A slight change in lighting, camera angle, or the reception desk’s position will change the algorithm’s output.

Reliability on a large scale requires a different approach than making the model for specific conditions. You can rely on our experience in adopting CV products on a large scale. We’ll help you prepare your solution for different conditions and data drift that affects the input data with time. 

Computer Vision in Hotel Industry Queue Monitoring

MLOps Will Help You Maintain and Scale the Solution to Your Growing Business Needs

Computer vision development must be monitored and maintained to adapt the solution to changing business needs, scenarios, and edge cases, maintaining product quality and preparing it to operate in broader settings for maximum value.

MLOps deploys and sustains machine learning models in workflow processes. It can help track and debug changes in the model’s parameters and enable adapting to real-time changes in data. It helps improve the model’s adaptability to changing environments and emerging scenarios with growing needs.

Computer Vision Development Process

Our Computer Vision Development Process

An effective computer vision solution must combine an understanding of software and hardware technologies, your business needs, and real-world scenarios and use cases

At every step of creating a machine vision product, our technology and business analysis experts will help you make the best decisions to ensure the success of your AI project in the short and long term.

Tell Us About Your Use Case, and We’ll Find the Technology

Our first meeting is usually to discuss your vision or goal for the product you want to develop. We’ll also want to know the target devices for your solution, as computers, smartphones, and cameras have different components and capabilities. The intended hardware will greatly impact the proposed solution. 

Next, our experts run workshops with you that translate your business goals and processes into detailed technical requirements. We can match these requirements with current knowledge of available solutions and research possible ways to build your CV product.

Expert Computer Vision Research and Development

Depending on its complexity, your idea might require an innovative approach beyond currently available open-source methods. We have PhD-level scientists on board, with their share in computer vision research and publications that further the progress of these technologies. They will combine scientific and technological expertise with skilled CV engineers to survey available technologies and determine which direction to take. If a completely new solution built from scratch is the best option, they will show you how to approach it via a proof of concept.

Computer Vision Proof of Concept Development

After thorough research, our experts will present you with a roadmap of the solution and how it would work to fulfill its purpose. A PoC and AI project roadmap aims to prove that the solution will answer your needs and determine what it would take to make it work. Please remember that PoC is often not a working product but more of a manifested concept, built as a jumping point to the right process and technology. After your approval, our team will work on an MVP to demonstrate and test the solution.

Computer Vision Minimum Viable Product Development

Developing an MVP is the stage at which the solution is already working, and you can test its efficiency. It allows us to examine it more thoroughly, inspect potential weaknesses, and determine how to fix them. The model might need more data for improved accuracy or better image quality. Continuous testing and improvements will ultimately ensure the desired results. If you want financing, an MVP can also be used for investors’ demonstrations. Ultimately, it evolves into a reliable product. However, it only works in these specific conditions and needs to be prepared for scaling.

Sometimes, a Pivot Is the Best Answer to Progress

We’re not afraid to tell you when it’s time to change the approach and pivot from the original technology. The tests may show that the current approach might not achieve the desired results. In such a case, pivoting from the original concept might be the optimal and quickest way to make things go in the right direction. Don’t be afraid to take this leap, which will help you save time and money in the long run. We have your back and will help you to make an optimal decision.

Mass Deployment and Scaling

Once the MVP meets the requirements, it’s time to prepare your product for further scaling and deployment. In our hotel example, mentioned earlier on the page, this would mean making a one-hotel MVP ready to work in the other 99 hotels. That’s where we’d engage our MLOps efforts to reinforce the technologies and prepare the product for changing conditions and scenarios, including edge cases. It allows you to replicate and adjust the solution to your needs in all environments.

Computer Vision Object Classification
Computer Vision Object Identification
Computer Vision Object Tracking

Object Classification

Simply put, vision systems can recognise objects and categorise them by sight. Similarly, the human brain immediately recognises that a cat is an animal. This task is essential for various applications, such as autonomous vehicles, security systems, and image retrieval. It is only a surface-level task, though, and involves labelling an entire image or detecting the presence of specific types of objects.

A drone with a camera can help a farmer with monitoring crop growth. Deep learning-based detectors can analyse video data, raise alerts on possible losses, and calculate the waste percentage. Automated monitoring systems can help increase security by automatically detecting intruders or thieves.

Object Identification

It’s a task that, on the surface, is similar to object classification. However, it’s more in-depth. It can recognise and distinguish individual instances of objects, even if they are of the same type. For example, in addition to recognising that a strawberry is a fruit, it will also acknowledge that it’s specifically a strawberry and not an apple or blueberry.

Object Tracking

It allows vision systems to follow an object in motion. For example, it can track the destination of a pedestrian at a train station or the eye movement on the screen of a smartphone user. It can be especially helpful in surveillance, sports analysis, and interactive systems like augmented reality.

Inspecting harvests can help detect diseases affecting crops and help find a solution to counteract them. Image-supported sorting stands can save manual labour by visually inspecting and automatically separating flawed plants.

Computer Vision Applications Across Industries

Each industry requires specific domain knowledge to quickly and effectively identify opportunities and implement AI solutions. Our domain expertise allows you to get the most out of your computer vision project, optimised for your organisation’s needs.

Computer Vision Solutions for Manufacturing and Warehousing industry

Computer Vision for Manufacturing and Warehousing

Examples of using AI-based vision technologies in these sectors include:

  • Quality control
  • Automation and robotics
  • Inventory management
  • Safety monitoring and inspection
  • Preventive maintenance
Computer Vision Solutions for Logistics industry

Computer Vision for Logistics

For Logistics and Transportation, the CV can be used for the following applications:

  • Automated sorting systems
  • Freight loading and unloading
  • Vehicle tracking and fleet management
  • Last-mile delivery
Computer Vision Solutions for Agriculture industry

Computer Vision for Agriculture

In agriculture, computer vision solutions can automate and increase productivity in tasks like:

  • Crop monitoring and management
  • Precision agriculture
  • Phenotyping
  • Harvesting
  • Livestock management
Computer Vision Solutions for Drone Manufacturing and Drone Users

Computer Vision for Drone Manufacturers and Users

Among others, computer vision solutions for drones involve:

Augment Your Computer Vision Team with the Combination of Science and Technological Knowledge

Our experts are fluent in the technological aspects of computer vision applications. With PhD-level scientists who contribute to the topic with their research papers, we can research it from scratch. We’ll use that knowledge to advise you on the best approach that will allow us to build the solution and scale it to meet your growing needs. And you are always the owner of the product.

If you already have a base for your CV efforts but need additional, experienced hands on deck, we’ll provide you with tech and R&D experts who will match your work culture.

Meet some of our CV specialists:

Marek Tatara, PhD

Chief Scientific Officer, Tech Lead

Assistant Professor at Gdańsk University of Technology, AI/ML Expert at M5 Technology, Member of the Polish Society For Measurement, Automatic Control And Robotics. works on the company’s research agenda and works on the implementation of both EU-funded and commercial R&D projects from the field of Computer Vision, Machine Learning and Embedded Systems.

Karol Duzinkiewicz

Senior Computer Vision Researcher

Seasoned engineer with many years of experience in international tech companies. Currently holds a team leader role in gaze estimation projects developed in the company.

Michał Ostyk

Computer Vision Engineer

A Computer Vision Engineer with experience in agriculture, fast food, sports analytics, and healthcare. He loves researching SOTA and converting it into an MVP in Pytorch. However, he recently delved deeper into MLops.

Jan
Glinko

Machine Learning Researcher

Graduated from the Faculty of Electronics, Telecommunications, and Informatics at the Gdansk University of Technology. He is interested in applying synthetic datasets for learning deep neural networks and in learning algorithms to reduce the amount of data required for effective network training.

Cezary
Polak

Machine Learning Researcher

Graduated from the Faculty of Electronics, Telecommunications, and Informatics at the Gdansk University of Technology. He is interested in using deep learning in biomedical engineering and generating synthetic data such as photos and texts

Artur
Skrzynecki

Machine Learning Researcher

Graduated from the Faculty of Electronics, Telecommunications, and Informatics at the Gdansk University of Technology. His areas of interest mainly focus on computer vision tasks, including biomedical data processing and deep neural network training and evaluation. Apart from that, he also enjoys web development topics

Jacek Niklewski, PhD

Data Scientist

Involved in projects related to computer vision, sports applications, medical diagnosis, and recommender systems. He graduated from the Computer Science degree in at Gdansk University of Technology. He has a MSc in Investment Management, a PhD in Finance, and a PgCert in Academic Practice in Higher Education at Coventry University.

Get in touch to see how our solutions can address your needs.

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Computer Vision Development Company

Technology Stack for Expert Computer Vision Development Services

  • OpenCV
  • MediaPipe
  • Python
  • PyTorch
  • FastApi
  • Docker
  • AWS
  • ClearML
  • DVC
docker
Python
PyTorch
ClearML
FastAPI
Azure logo
AWS
MediaPipe
OpenCV

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Send us an e-mail: [email protected]