PicPurify
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IMG.LY
Metaverse
imgix
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TensorFlow
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Scikit-learn
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The core algorithm behind PicPurify is built based on the most advanced deep learning technology. This algorithm is inspired by the human visual system, and is continuously learning how to identify specific contents in an image by scanning millions of them.
Picpurify use the most advanced deep-learning algorithms to deliver an unprecedented accuracy on the moderation of harmful content. That make us expert in computer vision problematics. Our company has trained and then fine-tuned several convolutional neural networks to perform various tasks of classification and detection over images in the context of filtering specific contents for companies.
We fully managed all the steps related to the creation of a deep learning model, starting from the data collection/annotation to the training and optimization of the algorithms. It allow us to provide tailor-made models to companies.
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Based on our record, TensorFlow seems to be more popular. It has been mentiond 7 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.
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 / over 1 year ago
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
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: about 2 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
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
Sightengine - Effortless moderation of user-submitted photos. Instantly detect nudity and adult content with our easy-to-use API, for a fraction of the cost of human moderation
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
IMG.LY - Power Your Apps with IMG.LY | The Leading Provider of Design, Photo, and Video Editing SDKs
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Metaverse - Democratized augmented reality platform: AR for everyone!
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
