Likelihood to Recommend Amazon Rekognition is well suited for all image and videos analysis. Also, deep learning projects for image and video can easily be done using this. It is very easy to use so a beginner can also use it.
Read full review Keras is quite perfect, if the aim is to build the standard Deep Learning model, and materialize it to serve the real business use case, while it is not suitable if the purpose is for research and a lot of non-standard try out and customization are required, in that case either directly goes to low level
TensorFlow API or
Pytorch Read full review Pros Image tagging is very good. Object detection is precise. Video tagging has become very easy using Rekognition. Read full review One of the reason to use Keras is that it is easy to use. Implementing neural network is very easy in this, with just one line of code we can add one layer in the neural network with all it's configurations. It provides lot of inbuilt thing like cov2d, conv2D, maxPooling layers. So it makes fast development as you don't need to write everything on your own. It comes with lot of data processing libraries in it like one hot encoder which also makes your development easy and fast. It also provides functionality to develop models on mobile device. Read full review Cons The cost is bit more for small scale companies. For text processing, OCR is not available in amazon rekognition. Only facial search is available in image search. Read full review As it is a kind of wrapper library it won't allow you to modify everything of its backend Unlike other deep learning libraries, it lacks a pre-defined trained model to use Errors thrown are not always very useful for debugging. Sometimes it is difficult to know the root cause just with the logs Read full review Usability Very much suitable for many applications where the image processing features are secondary and independent of any domain. This makes it a general solution and the recognition features are returned in a JSON object in response to the API called made which is a very simple process.
Read full review I am giving this rating depending on my experience so far with Keras, I didn't face any issue far. I would like to recommend it to the new developers.
Read full review Support Rating Support of Amazon is great. So far we are having a great experience using it.
Read full review Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.
Read full review Alternatives Considered It's easy to implement and its documentation is great compared to CNTK.
Read full review Keras is good to develop deep learning models. As compared to
TensorFlow , it's easy to write code in Keras. You have more power with
TensorFlow but also have a high error rate because you have to configure everything by your own. And as compared to
MATLAB , I will always prefer Keras as it is easy and powerful as well.
Read full review Return on Investment The best thing it made our work fast. It reduces the chance of failure of a project which is based on image or video processing. We can assign anyone in our team to work on this as it very easy to use. Read full review Easy and faster way to develop neural network. It would be much better if it is available in Java. It doesn't allow you to modify the internal things. Read full review ScreenShots