To develop a software that will help tag objects in images that can help create data sets for machine learning algorithms. This tool can then be used for many different purposes such as face detection, gender classification, weather forecasting, and many other areas that use artificial intelligence.
Image Tagging Tool for Computer Vision
To develop a software that will help tag objects in images that can help create data sets for machine learning algorithms. This tool can then be used for many different purposes such as face detection, gender classification, weather forecasting, and many other areas that use artificial intelligence. The aim is to create a tool that can easily create datasets of any nature that complement any machine learning algorithm and can make the use of artificial learning in any field easier.
The most important step to any computer vision project is to establish a clear objective for your machine learning algorithm to achieve. Your objective may vary widely based on your specific use case. It will determine the type and quantity of data required for a high quality computer vision dataset. Here are some common objectives:
1.Classification is one of the most common objectives for computer vision projects. It is also a strong foundation on which to combine other components to build more advanced vision systems.
2.Tagging is an objective that seeks to define an overall image with a series of labels. The output of this type of system might contain one label, two labels, X number of labels, or no labels.
3.Detection is the process by which vision systems find specific objects and localize them to a certain area within an image. If you care where in your image the object is found, this is your objective.
4.Tracking is a task involving both classification and detection (applying a label to an object and localization of that object within an image) that occurs repeatedly throughout a frame-by-frame series within a video.
5.Action recognition is an objective whereby a computer vision algorithm recognizes the position and orientation of the human body and can detect or predict actions as they occur in real-time. Some use cases for this function include posture analysis for security purposes, fall prevention in the elderly, or correcting movement imbalances in physical therapy. Posture recognition is also very popular by sports organizations to optimize training of specific movements such as pitching, punting, and swinging.
There are various data annotation tools already available like LabeLImg, VGG image annotator, etc., however they lack accuracy in annotating objects with irregular shapes.
The software will be developed by using python langugae and its Opeb CV Library.
This Software will be Web, Android or Desktop base.
The completed python application will consist of the following features:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Google Cloud subscription | Equipment | 1 | 8000 | 8000 |
| Web Hosting for 18 Months | Equipment | 1 | 31000 | 31000 |
| Amazon recognition API Access | Equipment | 1 | 6000 | 6000 |
| Total in (Rs) | 45000 |
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