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Caffe VS TFlearn

Compare Caffe VS TFlearn and see what are their differences

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Caffe logo Caffe

Caffe is an open source, deep learning framework.

TFlearn logo TFlearn

TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
  • Caffe Landing page
    Landing page //
    2019-06-12
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Caffe videos

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TFlearn videos

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Face Recognition using Deep Learning | Convolutional-Neural-Network | TensorFlow | TfLearn

Category Popularity

0-100% (relative to Caffe and TFlearn)

Caffe

TFlearn

Data Science And Machine Learning
39 39%
Data Science And Machine Learning
61% 61
OCR
13 13%
OCR
87% 87
Machine Learning
39 39%
Machine Learning
61% 61
AI
100 100%
AI
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Caffe and TFlearn

Caffe Reviews

7 Best Computer Vision Development Libraries in 2024
CAFFE, which stands for Convolutional Architecture for Fast Feature Embedding, is a user-friendly open-source framework for deep learning and computer vision. It was developed at the University of California, Berkeley, and is designed to be accessible for various applications.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
Caffe is a deep learning framework known for its speed and efficiency in image classification tasks. It comes with a model zoo containing pre-trained models for various image-related tasks. While it’s slightly less user-friendly than some other libraries, its performance makes it a valuable asset for high-speed image processing applications.
Source: clouddevs.com

TFlearn Reviews

We have no reviews of TFlearn yet.
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Social recommendations and mentions

Based on our record, TFlearn should be more popular than Caffe. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Caffe mentions (1)

  • Can someone please guide me regarding these different face detection models?
    Caffe is a DL framework just like TensorFlow, PyTorch etc. OpenPose is a real-time person detection library, implemented in Caffe and c++. You can find the original paper here and the implementation here. Source: almost 3 years ago

TFlearn mentions (2)

  • Beginner Friendly Resources to Master Artificial Intelligence and Machine Learning with Python (2022)
    TFLearn – Deep learning library featuring a higher-level API for TensorFlow. - Source: dev.to / almost 2 years ago
  • Base ball
    Both the teams in a game are given their individual ID values and are made into vectors. Relevant data like the home and away team, home runs, RBI’s, and walk’s are all taken into account and passed through layers. There’s no need to reinvent the wheel here, there's a multitude of libraries that enable a coder to implement machine learning theories efficiently. In this case we will be using a library called... - Source: dev.to / about 3 years ago

What are some alternatives?

When comparing Caffe and TFlearn, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

OpenCV - OpenCV is the world's biggest computer vision library

Clarifai - The World's AI

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

DeepPy - DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming.

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