darknet
vosk-api
darknet | vosk-api | |
---|---|---|
62 | 60 | |
21,466 | 7,085 | |
- | 2.2% | |
6.5 | 6.6 | |
4 days ago | 1 day ago | |
C | Jupyter Notebook | |
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
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Anybody building ML models in C++?
YoloV3/4 is C based if that counts: https://github.com/AlexeyAB/darknet
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[D] Fixing the angle of Skewed Paintings, see comments
This is all well-known information, see any (and all!) previous discussions when YOLOv5 comes up. For details: https://github.com/AlexeyAB/darknet/issues/5920
- Viseron 2.0.0 - Self-hosted, local only NVR and AI Computer Vision software.
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How do I train YOLO5 to detect small objects (arial imagery). something like 20-20 pixels or maybe little more? How do I increase resolution and apply augmentation and tiling? Or maybe the YOLO5 is not he best choice for that?
2) YOLOv5 is both slower and less precise than YOLOv4. Why use YOLOv5? Source: https://github.com/AlexeyAB/darknet/issues/5920
- Machine learning Library in C?
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I just realized yolov5 is GPL-3
So my recommendation is you stuck with Darknet/YOLO and use v4 of YOLO. The Darknet framework license is definitely suitable for commercial use: https://github.com/AlexeyAB/darknet/blob/master/LICENSE
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GPL vs MIT.
Still to long. Here's my favourite license: https://github.com/AlexeyAB/darknet/blob/master/LICENSE
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I was excited about YOLOv7, so I built a sharable object detection application with VDP and Streamlit.
When YOLOv7 was out, I built a web app to test it against the classic YOLOv4 and shared it with my team, then deployed it online to share with the community.
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Does reducing the number of classes on YOLOv5 make it faster at inference?
If you're worried about performance, you shouldn't be using YOLOv5 since it is slower (and less accurate!) than YOLOv4. Source: https://github.com/AlexeyAB/darknet/issues/5920
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[D] DarkNet YOLOv4 with CUDA 11.7 in Windows?
I looked around online but I only found this post discussing a related issue, leading me to think there seems to be some sort of compatibility issue going on here. And I think this is the most recent version of the file I am trying to compile located on the exact same folder where my copy is and when I opened it it shows CUDA 11.1 in line 307.
vosk-api
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Infini-Gram: Scaling unbounded n-gram language models to a trillion tokens
It's coming! CMUSphinx used to have something like this, and there are some [1] solutions [2] on the horizon.
[1]: https://github.com/alphacep/vosk-api/issues/55
[2]: https://github.com/outlines-dev/outlines?tab=readme-ov-file#...
- VOSK Offline Speech Recognition API
- Apollo dev posts backend code to Git to disprove Reddit’s claims of scrapping and inefficiency
- Working Vosk model?
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Creating a live transcript bot using Vosk Ai
So I don't know if my issue comes from my lack of knowledge of discord.js/voice or VOSK. so I guess the most important thing I need to see is if I am creating a proper stream for the Vosk API to capture the audio. if I can figure out how to capture an audio stream I can probably import that in to vosk and figure out how to use vosk myself. but right now I can't even get close! Thank you in advance...Sorry if this isn't the right place for this
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What are the aplications of rust in machine learning ?
I remember a while ago checking out the issues with Vosk speech recognition (written in C). A handful of it's issues are related to segfaults and null pointers.
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Show HN: Willow – Open-Source Privacy-Focused Voice Assistant Hardware
first, good initiative! thanks for sharing. i think you gotta be more diligent and careful with the problem statement.
checking the weather in Sofia, Bulgaria requires cloud, current information. it's not "random speech". ESP SR capability issues don't mean that you cannot process it locally.
the comment was on "voice processing" i.e. sending speech to the cloud, not sending a call request to get the weather information.
besides, local intent detection, beyond 400 commands, there are great local STT options, working better than most cloud STTs for "random speech"
https://github.com/alphacep/vosk-api
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ChatGPT API is now officially available, priced at $0.002 per 1k tokens
I did a one-off text to speech tool for someone last year and had pretty good results with VOSK. One upside is that it works offline, although I imagine if you use TTS a lot you'll notice issues I didn't.
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Looking to mod a Vector with GPT-3, what are my options?
You can use vosk-api (https://github.com/alphacep/vosk-api) to listen to your audio, transform it to text, and then post the text to GPT-3, then using the vector sdk, have your responses said by vector.
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A new voice assistant that looks promising
The set up script wants to download https://github.com/alphacep/vosk-api/releases/download/v0.3.45/vosk-model-en-v0.3.45.zip, but this resource is not found. AFAICT all releases never contained a model file. Remedy: hardcode one model from https://alphacephei.com/vosk/models. I guessed and picked the one with the closest name, vosk-model-en-us-0.22.zip, just so I could continue.
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
vosk-server - WebSocket, gRPC and WebRTC speech recognition server based on Vosk and Kaldi libraries
efficientdet-pytorch - A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
AutoSub - A CLI script to generate subtitle files (SRT/VTT/TXT) for any video using either DeepSpeech or Coqui
darknet_ros - YOLO ROS: Real-Time Object Detection for ROS
DeepSpeech - Install Mozilla DeepSpeech on a Raspberry Pi 4