nsfw_model
horovod
| nsfw_model | horovod | |
|---|---|---|
| 5 | 8 | |
| 1,611 | 13,952 | |
| - | 0.4% | |
| 0.0 | 5.2 | |
| 2 months ago | about 1 month ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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nsfw_model
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Any suggestions for client side or API content moderation tools for image uploads
I did some tests myself, and the results look very accurate. The model I use has 93% accuracy, and has been trained for days with over 60 GBs of data
- Blockchain will be great for MMORPGs, but the first few attempts with fail
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Looking for a suggestive nudity dataset
Link was not working for me (old.reddit.com). Here is another: https://github.com/GantMan/nsfw_model
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How To: NSFW Image detection on Digital Ocean Apps
Making predictions based on images involves two basic steps: training the data and then processing the prediction. How to train the ML model can be found in the Github repo: GantMan/nsfw_model.
- Is there a middleware or a common practise in webs with user accounts to check uploaded content is not offensive or pornographic?
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?
NudeNet - Neural Nets for Nudity Detection and Censoring
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.
ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
DeepDanbooru - AI based multi-label girl image classification system, implemented by using TensorFlow.
nsfwjs - NSFW detection on the client-side via TensorFlow.js
mpi4jax - Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap:
NSFW-FLASK - Flask app for detecting NSFW images
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
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.
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
thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries