darknet
serving
| darknet | serving | |
|---|---|---|
| 22 | 12 | |
| 25,292 | 6,071 | |
| - | 0.0% | |
| 0.0 | 9.8 | |
| about 1 month ago | 7 days ago | |
| C | C++ | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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.
darknet
- Llama.cpp: Full CUDA GPU Acceleration
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How to identify a senior developer
This reminds me of the resume for the guy who made darknet https://pjreddie.com/darknet/
- Anyone taking CS8803-O15: Computing Law?
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I can’t take this paper seriously anymore
Love the darknet (also made by him) github. Like what is this?
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YoloV7 Finally an official Yolo. This should actually be V5
I don’t know, the OG author seemed pretty lax on its use based on the license.
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I think this needs a post of its own
In that case you're sure to enjoy this one.
- Avoid negative output from yolo model
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Is there a functioning neural netowork or backbone written in pure C language only?
Literally the first google link dude… https://github.com/pjreddie/darknet
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Face Recognition
Election of tools: you should define if you are going to use machine/deep learning methods or classical approaches such as the Viola-Jones algorithm. I will recommend you to use ML/DL with TensorFlow (Object Detection API) or Darknet (YOLO).
- Show HN: An AI program to check videos for NSFW content
serving
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Llama.cpp: Full CUDA GPU Acceleration
Yet another TEDIOUS BATTLE: Python vs. C++/C stack.
This project gained popularity due to the HIGH DEMAND for running large models with 1B+ parameters, like `llama`. Python dominates the interface and training ecosystem, but prior to llama.cpp, non-ML professionals showed little interest in a fast C++ interface library. While existing solutions like tensorflow-serving [1] in C++ were sufficiently fast with GPU support, llama.cpp took the initiative to optimize for CPU and trim unnecessary code, essentially code-golfing and sacrificing some algorithm correctness for improved performance, which isn't favored by "ML research".
NOTE: In my opinion, a true pioneer was DarkNet, which implemented the YOLO model series and significantly outperformed others [2]. Same trick basically like llama.cpp
[1] https://github.com/tensorflow/serving
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[D] How do OpenAI and other companies manage to have real-time inference on model with billions of parameters over an API?
I mean, probably - it's written in C++ https://github.com/tensorflow/serving
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Should I wait for the M2 Macbook Pro?
We’re looking into that solution at the moment, the issue I’m referring to is related to this https://github.com/tensorflow/serving/issues/1948 we’ll know if the plug-in approach works for our uses soon but haven’t started looking into implementing it yet
- TF Serving has been unavailable for 9 days so far due to outdated GPG key
- TF Serving has been unavailable for 8 days
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Would you use maturin for ML model serving?
Which ML framework do you use? Tensorflow has https://github.com/tensorflow/serving. You could also use the Rust bindings to load a saved model and expose it using one of the Rust HTTP servers. It doesn't matter whether you trained your model in Python as long as you export its saved model.
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Is LaMDA Sentient? – An Interview [pdf]
Most likely it's a model server running something like https://github.com/tensorflow/serving and if there isn't a lot of load, the resource could kill some of its tasks. I wouldn't imagine it's sitting around pondering deep thoughts.
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Ask HN: How to deploy a TensorFlow model for access through an HTTP endpoint?
https://github.com/tensorflow/serving
https://thenewstack.io/tutorial-deploying-tensorflow-models-...
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Popular Machine Learning Deployment Tools
GitHub
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If data science uses a lot of computational power, then why is python the most used programming language?
You serve models via https://www.tensorflow.org/tfx/guide/serving which is written entirely in C++ (https://github.com/tensorflow/serving/tree/master/tensorflow_serving/model_servers), no Python on the serving path or in the shipped product.
What are some alternatives?
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
MNN - MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
flashlight - A C++ standalone library for machine learning
labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
XLA.jl - Julia on TPUs
tensorflow - An Open Source Machine Learning Framework for Everyone
oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
pytorch_nsfw_model - Pytorch model for NSFW classification with usage example
glow - Compiler for Neural Network hardware accelerators