HASS-Deepstack-object
yolov5
HASS-Deepstack-object | yolov5 | |
---|---|---|
2 | 129 | |
403 | 47,071 | |
- | 1.8% | |
5.3 | 8.8 | |
about 1 year ago | 5 days ago | |
Python | Python | |
MIT License | GNU Affero General Public License v3.0 |
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HASS-Deepstack-object
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Deepstack: Open-Source AI Server
Hi everyone, I am Moses Olafenwa, the CEO and Head of Operations of the company DeepQuest AI (now a UK company based in Greenwich, London). First, apologies for the missing information of our names on the about page. The deepquestai.com website hasn't been updated recently due to our team being a small one and having lots to do.
About DeepStack: DeepStack is an artificial intelligence server we developed late 2018 to empower developers to easily setup, integrate and leverage AI functionalities (blog post: https://medium.com/deepquestai/deepstack-build-ai-powered-ap... ) fully on the edge or their private cloud machines.
Today, DeepStack is available as a Docker image on Docker Hub and native application for Windows, with support for CPUs, modern NVIDIA GPUs, Jetson devices, ARM devices, Linux and MacOS with over 10 millions installs on Docker Hub ( https://hub.docker.com/r/deepquestai/deepstack ). It include functionalities such as Face Recognition/Detection APIs, common objects detection, image superresolution, custom detection models to detect any custom object of interest and many more. You can learn more about the product and using it via the documentation linked below
https://docs.deepstack.cc
DeepStack has a very active community on the official forum https://forum.deepstack.cc and other forums like HomeAssistant ( https://community.home-assistant.io/t/face-and-person-detect... ), IPCamTalk( https://ipcamtalk.com/tags/deepstack/ ) and YouTube ( https://www.youtube.com/results?search_query=deepstack+ai+se... )
From year 2019 after we released DeepStack till early, 2021 the project was largely developed and maintained by John Olafenwa (the creator of the AI server) and I; pretty hard for 2 folks with day job to keep up with everything involved in the project which is why some of our sites are not fully updated. That is about to change in 2022 as we grew to a team of 6 late last year and growing to ensure we keep developing, maintaining and improving DeepStack for the almost a million developers leveraging the server to integrate AI.
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For what do you use your Jetson Nano?
Running Deepstack on it, paired with HASS-Deepstack-object in Home Assistant.
yolov5
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จำแนกสายพันธ์ุหมากับแมวง่ายๆด้วยYoLoV5
Ref https://www.youtube.com/watch?v=0GwnxFNfZhM https://github.com/ultralytics/yolov5 https://dev.to/gfstealer666/kaaraich-yolo-alkrithuemainkaartrwcchcchabwatthu-object-detection-3lef https://www.kaggle.com/datasets/devdgohil/the-oxfordiiit-pet-dataset/data
- How would i go about having YOLO v5 return me a list from left to right of all detected objects in an image?
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Building a Drowsiness Detection Web App from scratch - pt2
!git clone https://github.com/ultralytics/yolov5.git ## Navigate to the model %cd yolov5/ ## Install requirements !pip install -r requirements.txt ## Download the YOLOv5 model !wget https://github.com/ultralytics/yolov5/releases/download/v6.0/yolov5s.pt
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[Help: Project] Transfer Learning on YOLOv8
Specifically what I did was take the coco128.yaml, added 6 new classes from Dataset A (which have already been converted to YOLO Darknet TXT), from index 0-5 and subsequently adjusted the indices of the other COCO classes. The I proceeded to train and validate on Dataset A for 20 epochs.
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Changing labels of default YOLOv5 model
I am using the default YOLOv5m6 model here with sahi/yolov5 library for my object detection project. I want to change just some of labels - for example when YOLO detects a human, I want it to label the human as "threat", not "person". Is there any way I can do it just changing some code, or I should train the model from scratch by just changing labels?
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First time working with computer vision, need help figuring out a problem in my model
You should add them without annotations. Go through this.
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AI Camera?
You are correct and if you check the firmware, it's yet another famous 3rd party project without attribution, namely https://github.com/ultralytics/yolov5
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First non-default print on K1 - success
On one side, being a Linux user for 24 years now, it annoys me that they rip off code and claiming it as theirs again, thus violating licenses, but on the other thanks to k3d's exploit I'm able to tinker more with the machine and if needed do (selective) updates by hand then with a closed source system. It's not just "klipper", with klipper, fluidd and moonraker, it's also ffmpeg and mjpegstreamer. It's gonna be interesting since they also use a project that isn't just GPL, but APGL (in short "If your software gives service online, you have to publish the source code of it and any library that it borrows functions from.") - they use yolov5 (for AI).
- How does the background class work in object detection?
What are some alternatives?
frigate - NVR with realtime local object detection for IP cameras
mmdetection - OpenMMLab Detection Toolbox and Benchmark
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
DeepStack - The World's Leading Cross Platform AI Engine for Edge Devices
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
OpenCV - Open Source Computer Vision Library