NudeNet
horovod
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| NudeNet | horovod | |
|---|---|---|
| 7 | 8 | |
| 832 | 13,952 | |
| - | 1.0% | |
| 3.6 | 5.2 | |
| over 2 years ago | about 1 month ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
NudeNet
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Need categorising topless images
https://github.com/notAI-tech/NudeNet - This is how to use it
- Can someone Github project to Chrome extension?
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lewdstopper: a Discord bot to automatically remove NSFW images outside of #NSFW
Hi all! I recently came up with a Discord bot that automatically removes NSFW images outside of #NSFW. It uses a neural network made by notAI-tech (NudeNet) to make these decisions, has configuration for everything you'd need, has pretty embeds for alerts, and is asynchronous so the bot wont get held up on every image.
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A bit of a problem involving a wife wanting family pictures, a deceased husband, and 10+TB of files mostly containing porn.
Try NudeNet - it's not super user friendly to run but you should be fine since it sounds like you have some experience. It's the only thing I know of.
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[OC] Percentage of nudity by years in the Playboy Magazines
I used NudeNet, everything is detailed on their github page
horovod
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Discussion Thread
Broke: using Horovod
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[D] What is the recommended approach to training NN on big data set?
And in case scaling is really important to you. May I suggest you look into Horovod?
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Anyone know of any papers or models for segmenting satellite images of a city into things like roads, buildings, parks, etc?
Training is not the same as inference (doing the segmentation), so that scale is probably off by a lot. One or two orders of magnitude just depending on the specifics of what hardware you're running on, and your training and eval dataset would be several orders of magnitude smaller. FAANGs would parallelize that training as well (don't remember if UNet is inherently parallelizable for training) via their internal equivalent of Horovod, so they'll do a GPU-month worth of training in less than a day.
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Embedding Python
[[email protected]] match_arg (utils/args/args.c:163): unrecognized argument quiet [[email protected]] HYDU_parse_array (utils/args/args.c:178): argument matching returned error [[email protected]] parse_args (ui/mpich/utils.c:1639): error parsing input array [[email protected]] HYD_uii_mpx_get_parameters (ui/mpich/utils.c:1691): unable to parse user arguments [[email protected]] main (ui/mpich/mpiexec.c:127): error parsing parameters I believe this is due to mpich being installed: https://github.com/horovod/horovod/issues/1637
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[D] PyTorch Distributed Training Libraries: What are the current options?
Check out Horovod - https://github.com/horovod/horovod
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[D] GPU buying recommendation
If you just want to run tensorflow or pytorch for a Jupyter notebook, setting the environment shouldn't be difficult. I know that AWS has a marketplace of preconfigured images. However, you can go as advanced as setting up a cluster of gpu-equipped nodes to setup Horovod (https://github.com/horovod/horovod) to do distributed machine learning. Yes, there's a learning curve, but you cannot acquire this skillet any other way.
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SKLean, TensorFlow, etc vs Spark ML?
I'm the maintainer for an open source project called Horovod that allows you to distribute deep learning training (e.g., TensorFlow) on platforms like Spark.
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Cluster machine learning
You'll want to use horovod to run keras in a distributed system. Then use Slurm to manage the cluster and run the job.
What are some alternatives?
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
petastorm - Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
nsfw_model - Keras model of NSFW detector
DeepDanbooru - AI based multi-label girl image classification system, implemented by using TensorFlow.
NudeNet-models - Pre-trained models for https://github.com/bedapudi6788/NudeNet
mpi4jax - Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap:
pytorch2keras - PyTorch to Keras model convertor
onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
test-lists - URL testing lists intended for discovering website censorship
thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
Finance-Using-Python - This product helps to understand the stocks in visual manner and as well as it saves the record. And help to predict the data
seq2seq - A general-purpose encoder-decoder framework for Tensorflow