Get Ahead with Computer Vision Services and Solutions
Take advantage of the potential of Computer Vision solutions and enjoy world-class Computer Vision Services. At Addepto, we offer computer vision services that perfectly match the unique needs of our clients. Open your business to new, high-tech opportunities.
Grow your business and improve operations with computer vision services
In order to develop an effective digital product, it is necessary to understand and find a way to answer users’ needs. According to them, we implement the right high-tech solution which will boost the efficiency of processes as well as user experience.
To ensure a successful implementation you need to cooperate with a trusted partner, experienced, and strict in following reliable methods.
Why should you consider AI computer vision services?
A short guide to applying Computer Vision services
Computer vision (CV) is an artificial intelligence-based technology that allows computers to observe the world. By analyzing visual data, this innovation can almost perfectly understand a particular situation, and without missing any factors, find the best solutions or the most reasonable decisions.
Which companies use Python?
Python is a trusted high-level programming language used for software applications. It is a trusted program, used by big companies like Google, NASA, Yahoo!, Wikipedia, and many more.
Examples of computer visions services:
Object Detection is one of Computer Vision Services which focuses on detecting various objects on photos like cats, dogs, cars, bikes, humans, etc., by extracting features from pixels and applying deep learning to recognize patterns. One of the main areas of object detection is face recognition.
Image and Video Pre-Processing
Advanced Computer Vision with the use of neural networks can perform image transformations not available for traditional image processing algorithms. As an example, we can artificially increase the number of trees or remove them without noticing an artificial change.
It is possible to generate missing parts of the photo or change the sky’s appearance from Earth to Mars. Possibilities of image enhancing and transformation are limitless and require just creating a specialized model for a given task.
Traditionally, to detect an object on an image it used to be sufficient to just select its position by the rectangle.
Now, an improvement of this technique is outlining the given object (for example by a slight change of its color) and in that way segment image on different objects where the result is obtaining an image very similar to the stained glass.
This technology will be extensively used in autonomous navigation and radiology (outlining cancerous changes in tissue).
Areas where computer vision services could be applied:
- Digital twin
- Quality control
- Robotic process automation
… and many more.
Computer vision solutions and services – case studies
Case Study 1 – Demographic analysis
An influencer marketing platform wanted to create a solution for demographic analysis of influencer recipients. Additional functions and deeper analysis of the audience were needed. Financial factors were also important, the solution should be more cost-effective than a 3rd party vendor.
Addepto has developed a machine learning solution that extracts and processes data from various social media sources using Big Data techniques.
With the help of Machine learning models solutions automatically extract knowledge from text and images age, family status, personal income, ethnicity, occupation, interests, brands, sentiment.
For computer vision was used deep neural network object detector such as SSD and YOLO trained on a large corpus of manually labeled data (81% accuracy for gender recognition).
The solution helped the company to flexibly manage the analysis of influential audiences, obtain more precise results, and reduce overall costs. In the long run, our solution may enable a company to gain a competitive advantage.
Case Study 2 – Fast image processing
Polish retailer owns thousands of pictures of product labels. Our task was to automatically find the place where the ingredients are written and transform the images into text.
We used a modified VGG16 convolutional neural network to find boxes containing ingredients information – as similar to ground truth boxes as possible (91% accuracy). The extracted boxes were used in Google OCR to extract text data.
After extracting the text data, we processed the text using NLP techniques and categorized the product. The algorithm has been integrated with the mobile application.
Our solution processes images much faster than it is possible manually, helping people choose the right food to eat if someone has allergies. Moreover, it examines if the product changes over time.