HASS-Deepstack-object
Mask_RCNN
HASS-Deepstack-object | Mask_RCNN | |
---|---|---|
2 | 28 | |
403 | 24,169 | |
- | 0.5% | |
5.3 | 0.0 | |
about 1 year ago | 4 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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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.
Mask_RCNN
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Intuituvely Understanding Harris Corner Detector
The most widely used algorithms for classical feature detection today are "whatever opencv implements"
In terms of tech that's advancing at the moment? https://co-tracker.github.io/ if you want to track individual points, https://github.com/matterport/Mask_RCNN and its descendents if you want to detect, say, the cover of a book.
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Analyze defects and errors in the created images
Mask R-CNN
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List of AI-Models
Click to Learn more...
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Thought Dump About Recent AI Advancements And Palantir
- Mask RCNN https://github.com/matterport/Mask_RCNN (open source, so also not Palantir's)
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Why are python dependencies so broken?
pip install git+https://github.com/matterport/Mask_RCNN
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DeepCreamPy & Hent-AI Guide: Installation and anime censorship removal (Version 2)
It is important to realize that to do its masking procedures, Hent-AI uses the Mask RCNN (MRCNN) package from Matterport. The problem with this version of MRCNN is that it is not compatible with Tensorflow 2.X versions, essentially limiting Hent-AI compatibility to strict Tensorflow 1.X versions. Since Tensorflow 1.15 is the last of the Tensorflow 1.X versions and uses CUDA 10.0, which supports a maximum compute capability of 7.5, this means that the last NVIDIA GPU series that is compatible with the original Hent-AI implementation is the RTX 2000 series. This is, of course, not optimal since it means that RTX 3000 series and later GPUs cannot be used despite their significant computing power and high VRAM.
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[P] Mask R-CNN (matterport) does not generate masks or just generates them randomly
I read that it could bethe problem with scipy version (https://github.com/matterport/Mask_RCNN/issues/2122) so I downgraded it, I also tried to modify shift = np.array([0, 0, 1., 1.]) in utils.py but nothing helped.
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Mask RCNN importing error
I am assuming you did a pip install of this github repository, or did you run pip install mrcnn. The mrcnn package on pypi is just an example package and doesn't have any useful functionality. In addition, where did you get the code from that you are trying to run, from someone else or did you write it yourself? Reason I am asking is because the import error is to be expected since there indeed is no InferenceConfig class defined in mrcnn.visualize.
- Maskrcnn - Mask r-cnn for object detection and segmentation
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MRCNN TF==2.7.0
Hello AI learners, check out my own development of Mask-RCNN supporting Tensorflow2.7.0 and Keras2.8.0. This is an edit of MRCNN which supports Tensoflow1.0, only.
What are some alternatives?
frigate - NVR with realtime local object detection for IP cameras
Swin-Transformer-Object-Detection - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
yolact - A simple, fully convolutional model for real-time instance segmentation.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
mmdetection - OpenMMLab Detection Toolbox and Benchmark
ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
mmsegmentation - OpenMMLab Semantic Segmentation Toolbox and Benchmark.
DeepStack - The World's Leading Cross Platform AI Engine for Edge Devices
Mask-RCNN-training-with-docker-containers-on-Sagemaker
Mask-RCNN-Implementation - Mask RCNN Implementation on Custom Data(Labelme)