Google Vision AI VS TensorFlow

Google Vision AI

Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.

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.

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2023-09-28

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2023-06-19

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What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

Category Popularity

0-100% (relative to Google Vision AI and TensorFlow)

Google Vision AI

TensorFlow

OCR

100 100%

OCR

0% 0

Data Science And Machine Learning

0 0%

Data Science And Machine Learning

100% 100

Image Analysis

100 100%

Image Analysis

0% 0

AI

14 14%

AI

86% 86

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Vision AI and TensorFlow

Google Vision AI Reviews

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TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024

From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.

Source: www.labellerr.com

10 Python Libraries for Computer Vision

TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.

Source: clouddevs.com

25 Python Frameworks to Master

Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.

Source: kinsta.com

Top 8 Alternatives to OpenCV for Computer Vision and Image Processing

TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...

Source: www.uubyte.com

PyTorch vs TensorFlow in 2022

There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...

Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, Google Vision AI should be more popular than TensorFlow. It has been mentiond 41 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.

Google Vision AI mentions (41)

Ask HN: Please recommend me an NSFW content detection API
I've been trying out Google's Cloud Vision API (https://cloud.google.com/vision) as a means of detecting NSFW content in user-submitted images but am finding it surprisingly unreliable. A large proportion of requests appear to just randomly hang before timing out with no error. I'm looking for recommendations for an alternative solution which can flag images containing pornography, gore, violence, etc. All the bad... - Source: Hacker News / 8 months ago
NASA Image Of Apollo 17 Landing Site Featuring A TR-3B Patented Triangle Shaped Craft
I wonder if we could use something like https://cloud.google.com/vision to employ AI image classification on these sat images? Source: 10 months ago
Picture Recognition
There are many. Google Lens can classify images. It can even identify species of plants and animals. If by "toolset" you mean you want an API to write your own applications, you can use the Google Vision API. Source: 10 months ago
I work at a non-tech company and have been asked to make software that is impossible. How do I explain it to my boss?
Could you use Vision AI for this maybe? Source: 11 months ago
just finished the thumbnail to my 8th gaming video. any critiques? anything i should add, remove, change in your opinion? just trying to perfect my craft as best as possible. the vid is just simple gameplay btw
The violence will get it not recommended, use https://cloud.google.com/vision/ to see what I'm talking about. It comes up as very racy and possibly adult. Source: 12 months ago

TensorFlow mentions (7)

Creating Image Frames from Videos for Deep Learning Models
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / about 1 year ago
Need help with a Tensorflow function
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 2 years ago
Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: almost 2 years ago
[Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
[Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 2 years ago