Amazon Rekognition Pros and Cons

The core strength of Amazon Rekognition is the image recognition. The accuracy of results are so good. False positive are very less. Review collected by and hosted on G2.com.

There is learning curve and price can be furthor reduced. Review collected by and hosted on G2.com.

One of the most impressive aspects of Amazon Rekognition is its robustness in image and video analysis. It excels in accurately identifying objects, scenes, and faces within images and videos, enabling powerful content analysis and search functionalities. Its facial recognition capabilities are particularly noteworthy, allowing for facial analysis, verification, and indexing at scale. Additionally, its integration with other AWS services and ease of use through APIs make it an efficient tool for developers and businesses looking to implement sophisticated image and video analysis functionalities in their applications. Review collected by and hosted on G2.com.

One of the concerns regarding Amazon Rekognition, as with any facial recognition technology, revolves around potential privacy and ethical implications. There have been discussions about the use of such technology in surveillance, raising issues related to privacy violations and the potential for misuse. Additionally, there have been concerns about the accuracy of facial recognition algorithms, especially in terms of potential biases and errors, which could lead to incorrect identifications or perpetuate societal biases. It's essential to approach the use of facial recognition technology with careful consideration of these ethical and privacy-related aspects. Review collected by and hosted on G2.com.

The ability to analyze and identify objects, people, text, scenes, and activities in images and videos is accurate. Its versatility makes it valuable. Easy to implement and easy to use.

Customer service is 24x7 and easy integration. Review collected by and hosted on G2.com.

privacy issues, especially regarding facial recognition technology. Critics worry about its use in surveillance and the implications for individual privacy and civil liberties. Review collected by and hosted on G2.com.

I like the fact that Amazon Rekognition is very efficient in recognizing the elements in photos or videos without extensive training. It is a handy tool if we don't want to go to the roots of the Computer Vision models and just focus on the implementation. Review collected by and hosted on G2.com.

Sometimes, when the prebuilt model is not able to recognize certain details it gets difficult to get workarounds. Review collected by and hosted on G2.com.

Ease of use. Less development time with integration. Review collected by and hosted on G2.com.

The result set ie the output set is often not easy to interpret. Depending on the subject, the system autogenerates JSON making interpretation much more nested. Real time large scale implementation is bit of a challenge with SaaS. At times, the sofware goofs up by not making the right accurate prediction ariticulation. Review collected by and hosted on G2.com.

Easy to use API, very classified packages for reference.

Can easily configure various requirements. Review collected by and hosted on G2.com.

Till now no complaints, the response is perfect with all details depends on how we need to use them. Review collected by and hosted on G2.com.

The most liked thing about Amazon Rekognition is it is straightforward to use; It provides video analytics output in a Visual way. I can see the identified objects in the square boundary. I liked the ease of use. Also it has great documentation Review collected by and hosted on G2.com.

The thing which I don't like about Amazon Rekognition is the JSON output after video analytics completion. It is a bit complex and difficult to interpret. Review collected by and hosted on G2.com.

It is so easy to integrate with my project. I used it for the user login via the face. It can easily distinguish between person who is far and who is close. And even can recognize when Review collected by and hosted on G2.com.

They don't have to identity a specific object. Like if given water bootle and soda bottle, it will predict it as a bottle. But are doing good and hopefully one day they will achieve that. Review collected by and hosted on G2.com.

Its smooth and high accuracy compared to other open source ocr libs Review collected by and hosted on G2.com.

Its quite expensive if you use it on a scale but for our use case its cheap Review collected by and hosted on G2.com.

The best part about Amazon Rekognition is its ease of use and simplicity to understand. When I was first tasked to look into this product, the company was doing a Hack Day. In the span of a day I managed to build a website that was able to take given images and determine whether the image contained a duck or not. This allowed me to understand how simple it was to use Amazon Rekognition. Review collected by and hosted on G2.com.

I felt like the documentation for setting up and using the product was alright. Although was lacking support in PHP for some major components. Other than that, the setup and use was easy. However I would improve the documentation.

Also, I found that some of the products features were limited and could be improved upon over time to include additional features and have a smarter model. Many of the images the API responded with no response rather than something even though it was a valid image with normal content inside. Review collected by and hosted on G2.com.