Analyze easily images with AI: Object Detection
Tags: objectdetection, ai, api
Published: 2022-08-05 14:07:47

_This article is brought to you by the Eden AI team. We allow you to test and use in production a large number of AI engines from different providers directly through our API and platform. You are a solution provider and want to integrate Eden AI, contact us at : contact@edenai.co_

## Intro:

In this article, we are going to see how we can easily integrate an Object Detection engine in your project and how to choose and access the right engine according to your data.

## Definition:

Object detection is a computer vision technique that works to identify and locate objects within an image or video. Specifically, object detection draws bounding boxes around these detected objects, which allow you to locate where objects are in a given scene. Object detection is different from image recognition which labels an entire image:


## History:

In the beginning of the 2000s, the first object detection engines were handmaded due to the lack of effective image representation at that time.

Originally proposed in 2005 by N. Dalal and B. Triggs, the Hog Detector is an improvement of the scale invariant feature transform and shape contexts of its time.HOG works with something called blocks, a dense pixel grid in which gradients are constituted from the magnitude and direction of change in the intensities of pixels within the block. HOGs are widely known for their use in pedestrian detection. To detect objects of different sizes, the HOG detector rescales the input image for multiple times while keeping the size of a detection window unchanged.

Between 2005 and 2015, multiple object detection evolutions were created: Deformable Part-based Model (DPM) then deep learning approaches (AlexNet, RCNN? SSPnet, FastRCNN, FPN, etc.).

## Use cases:

You can use Object Detection in numerous fields, here are some examples of common use cases:

- Retail: Customer Behavior Tracking and current number of people in the store can be counted
- Agriculture: Object detection engine is useful for Wheat Rust disease detection. It allows farmer to react to potential problem areas at an early stage
- Healthcare: object detection engines specially trained to detect diseases / medical stuff
- Automotive Industry: car detection, licence plate detection
- Fitness: Human Pose Estimation

## The Multi cloud approach

When you need a Object Detection engine, you have 2 options:

- First option: multiple open source Object Detection engines exist, they are free to use. Some of them can be performant but it can be complex to set up and use. Using an open source AI library requires data science expertise. Moreover, you will need to set up a server internally to run open source engines.
- Second option: you can use engines from your cloud provider. Actually, cloud providers like Google Cloud, AWS, Microsoft Azure, Alibaba Cloud or IBM Watson are all providing multiple AI engines often including Object Detection. This option looks very easy because you can stay in a known environment where you might have abilities in your company and the engine is ready-to-use.
The only way you have to select the right provider is to benchmark different providers’ engines with your data and choose the best OR combine different providers’ engines results. You can also compare prices if the price is one of your priorities, as well as you can do for rapidity.

This method is the best in terms of performance and optimization but it presents many inconveniences:

- you may not know every performant providers on the market
- you need to subscribe and contract with all providers
- you need to master each providers API documentation
- you need to check their pricings
- You need to process data in each engine to realize the benchmark

Here is where Eden AI becomes very useful. You just have to subscribe and create an Eden AI account, and you have access to many providers engines for many technologies including Object Detection. The platform allows you to benchmark and visualize results from different engines, and also allows you to have centralized cost for the use of different providers.

Eden AI provides the same easy to use API with the same documentation for every technology. You can use the Eden AI API to call Object Detection engines with a provider as a simple parameter. With only a few lines, you can set up your project in production.

## Test:

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/dupwt8f488arabqoukne.png) 
Eden AI SDK for Explicit Content Detection

### Result:

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/zgh4q0r69f7t6rljky16.png)
Eden AI SDK result for Explicit Content Detection

### Platform:

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/kg39vczb47dxcbwkrpen.png) 
Eden AI Platform for Object Detection

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/116t42edr7h7w67v61ob.png) 
Eden AI Platform result for Object Detection

## Conclusion:

There are numerous Object Detection engines available on the market: it’s impossible to know all of them, to know those who provide good performance. The best way you have to integrate Object Detection technology is the multi-cloud approach that guarantees you to reach the best performance and prices depending on your data and project. This approach seems to be complex but we simplify this for you with Eden AI which centralizes best providers APIs.