The app uses computer vision to detect and change the color of objects. Our solution uses the phone’s camera to detect the object. After that, it’s possible to change the color. ColorDetection is fast and straightforward to use.
We’ve created a simple solution that changes the colors of the chosen objects using computer vision.
Create an open-source app based on Swift and OpenCV that uses computer vision to track objects and change their colors.
Detecting the planes where to change colors
Integrating nine popular colors
Implementing the ability to edit color saturation
Our team created an iOS app based on Swift and OpenCV. ColorDetection app allows changing the color of an object choosing from nine popular options.
Computer vision uses pictures and videos to understand a real-world scene.
Computer vision can
Identify objects on images or videos.
Track things that are moving.
Measure the real-world size or estimate the distance from the camera.
Detect objects even if they change size or orientation.
Classify things on the video or photo.
Image classification. Receiving many examples of the image class for computer vision machine learning.
Object detection. Defining the objects in the image and labeling them.
Object tracking. Following one or more moving objects in the scene.
Semantic segmentation. Dividing the entire picture into groups of pixels that can be labeled and classified.
Main features of the project
A powerful backend of the app has transformed into two main features.
Changing object color
The main feature of ColorDetection is changing the color of the chosen object in a real-time mode. The user can choose from nine colors. It’s required to tap on the item and pick the color from the list.
After picking the new color, the user can change the saturation of the picked color. Also, it’s possible to set the height, volume, and space of the object.
The following tools were used to develop Face Detection App:
Visit our GitHub account to look through the open code of this library.
Feel free to read a detailed case study on how to develop computer vision features with OpenCV.