What users are saying about
3 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>
Score 7 out of 100
17 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>
Score 8.5 out of 100

Likelihood to Recommend

Caffe Deep Learning Framework

Caffe is only appropriate for some new beginners who don't want to write any lines of code, just want to use existing models for image recognition, or have some taste of the so-called Deep Learning.
Anonymous | TrustRadius Reviewer

Keras

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
Anonymous | TrustRadius Reviewer

Pros

Caffe Deep Learning Framework

  • Caffe is good for traditional image-based CNN as this was its original purpose.
Anonymous | TrustRadius Reviewer

Keras

  • 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.
Gaurav Yadav | TrustRadius Reviewer

Cons

Caffe Deep Learning Framework

  • Caffe's model definition - static configuration files are really painful. Maintaining big configuration files with so many parameters and details of many layers can be a really challenging task.
  • Besides imagine and vision (CNN), Caffe also gradually adds some other NN architecture support. It doesn't play well in a recurrent domain, so we have to say variety is a problem.
  • Caffe's deployment for production is not easy. The community support and project development all mean it is almost fading out of the market.
  • The learning curve is quite steep. Although TensorFlow's is not easy to master either, the reward for Caffe is much less than the TensorFlow can offer.
Anonymous | TrustRadius Reviewer

Keras

  • 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
Rounak Jangir | TrustRadius Reviewer

Usability

Caffe Deep Learning Framework

No score
No answers yet
No answers on this topic

Keras

Keras 7.7
Based on 2 answers
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.
Saurabh Kumar | TrustRadius Reviewer

Support Rating

Caffe Deep Learning Framework

No score
No answers yet
No answers on this topic

Keras

Keras 8.2
Based on 2 answers
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.
Saurabh Kumar | TrustRadius Reviewer

Alternatives Considered

Caffe Deep Learning Framework

TensorFlow is kind of low-level API most suited for those developers who like to control the details, while Keras provides some kind of high-level API for those users who want to boost their project or experiment by reusing most of the existing architecture or models and the accumulated best practice. However, Caffe isn't like either of them so the position for the user is kind of embarrassing.
Anonymous | TrustRadius Reviewer

Keras

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.
Raghuvar Prajapati | TrustRadius Reviewer

Return on Investment

Caffe Deep Learning Framework

  • Since we stopped using Caffe before it can reach the production phase, there is no clear ROI that can be defined.
Anonymous | TrustRadius Reviewer

Keras

  • 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.
Rakesh Kumar | TrustRadius Reviewer

Pricing Details

Caffe Deep Learning Framework

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Keras

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Add comparison