Top 23 Python object-detection Projects
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLiteProject mention: Equations for computing true positives and false positives when using object detection algorithms? | reddit.com/r/artificial | 2022-01-13
Looking at this source (https://github.com/ultralytics/yolov5/issues/5713), I found that you could calculate the true positives and false positives with the following equations:
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlowProject mention: Open source - that means free to use commercially right? ... right? | reddit.com/r/deepdream | 2021-12-04
Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.
OpenMMLab Detection Toolbox and BenchmarkProject mention: I want to create a pill counter using points instead of bounding boxes. What model should I train from? | reddit.com/r/learnmachinelearning | 2022-01-01
If you are really that lazy: use bboxes of the fixed size placed in the center of the pill. The pill does not have to fit into the box - modern architectures see the image as a whole, not only the crop in the box. For example if you would train detection on labels which are shifted (add 30px to each label coordinate), the network would learn to place each box 30px next to the actual object. So just let small box represent the center of the pill. The problem will arise if you will use improperly configured architecture, i.e. if you will not change the anchors in SSD model. Try efficientdet architecture implemented in mmdetection or, the easiest, yolov5. These should work out of the box.
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125Project mention: Data augmentation strategies for object detection? Could you point me to good resources or best practices you know of? | reddit.com/r/computervision | 2021-10-30
You can definitely look at Albumentation - we had a ton of success working with this library https://github.com/albumentations-team/albumentations
YOLOv3 in PyTorch > ONNX > CoreML > TFLite (by ultralytics)Project mention: I don't know how to train a YOLO v3 model with some custom data that is labeled in an unusual form (XML files) | reddit.com/r/learnmachinelearning | 2021-10-29
Each image has an XML file associated with it. The XML files have the corresponding labels and bounding boxes, so I can write a script to convert them into this form, and follow this tutorial on training custom data.
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilitiesProject mention: Sort Image Files | reddit.com/r/learnpython | 2021-08-26
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.Project mention: Imagine what historians will say about naming convention for pre trained models in 50 years… | reddit.com/r/datascience | 2021-12-11
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
AutoGluon: AutoML for Text, Image, and Tabular DataProject mention: What will the data science job market be like in 5 years? | reddit.com/r/datascience | 2021-08-14
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
NVR with realtime local object detection for IP camerasProject mention: Self hosted open source video surveillance suggestions? | reddit.com/r/selfhosted | 2022-01-25
A Unified Toolkit for Deep Learning Based Document Image AnalysisProject mention: Extract text from PDF | reddit.com/r/Python | 2021-11-02
One of the tools I'm excited about (but haven't used in production) is LayoutParser. It's open-source, and can do some document image analysis especially on non-generic docs.
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.Project mention: [P] Object detection framework : Detectron2 VS MMDetection | reddit.com/r/MachineLearning | 2021-09-29
There are also some nice methods built on Detectron2 in [AdelaiDet](https://github.com/aim-uofa/AdelaiDet).
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object DetectionProject mention: Beginner : Object (shape) detection in binary images | reddit.com/r/pytorch | 2021-05-15
I have also experimented with SSD300 models from this example : https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Object-Detection but again, I think the lack of RGB/greyscale data makes this largely useless ?
OpenMMLab's next-generation platform for general 3D object detection.Project mention: Master thesis on autonomous vehicles (cybersecurity aspect) | reddit.com/r/AutonomousVehicles | 2021-07-17
You create and test the attacks on datasets like Kitti, NuScenes, and many others. Basically you try to manipulate the input to a certain detection pipeline for example (You can find a lot of LiDAR and camera based detection pipelines here: https://github.com/open-mmlab/mmdetection3d and here https://github.com/open-mmlab/mmdetection). You try to manipulate the input so that it deceives the car to do what you need without having control to the car itself.
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tfliteProject mention: Object tracking on Android | reddit.com/r/computervision | 2021-07-25
A Keras port of Single Shot MultiBox DetectorProject mention: Shared weights between different implementations | reddit.com/r/learnmachinelearning | 2022-01-01
Yeah, the order of axes was different between those 2. Another guy used https://github.com/pierluigiferrari/ssd_keras https://github.com/uhfband/keras2caffe/blob/master/keras2caffe/convert.py probably not much actual use but maybe some more reassurance?
Scaled-YOLOv4: Scaling Cross Stage Partial NetworkProject mention: Real time object detection and recognition | reddit.com/r/learnmachinelearning | 2021-11-08
Take a look at yolov5 or scaled yolov4. They should both handle real-time training, at low enough resolution anyway; I don't know if there is any model that can do real-time detection on 4K videos. Don't pay attention to the version numbers, I think the scaled yolov4 is sliiiightly better performance.
Training and Detecting Objects with YOLO3 (by experiencor)Project mention: What’s Destroying My Yard? Pest Detection with Raspberry Pi | news.ycombinator.com | 2021-10-01
I've always been facinated by the usage of the Pi. I think of the methods used when you have a pi, versus not having one. It looks like a fun project if you have all the parts, but I don't so I thought of this alternative!
A method I thought of was just a camera that will utilize yolo3 https://github.com/experiencor/keras-yolo3 or just an always on security camera that you can just skip through the video to see all the activity with less setup, and seeing what animals cause issues. The jetson for faster 'edgey' visual ML models might be an option for those who want a stronger NPU, but using online GPU/NPU tokens and GPUs on computers if you don't need live feedback is very effective.
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.Project mention: What is the Yolov4 MakeFile Config for 3080 GPU? | reddit.com/r/tensorflow | 2021-09-17
Refer to this https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras/ as a beginner's reference guide. Then look at this https://github.com/wizyoung/YOLOv3_TensorFlow to further enhance your knowledge.
SECOND for KITTI/NuScenes object detection (by traveller59)Project mention: Linux / Nvidia systems needed for AI specialization? | reddit.com/r/OMSCS | 2021-11-24
Exactly this, we were working with: https://github.com/traveller59/second.pytorch
TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNetProject mention: Jetson Nano: TensorFlow model. Possibly I should use PyTorch instead? | reddit.com/r/pytorch | 2021-06-04
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weightsProject mention: Bounding box annotations and object orientation | reddit.com/r/computervision | 2021-08-26
However, there are papers on oriented object detectors (see https://arxiv.org/pdf/1911.07732.pdf) for example. In that paper, they do achieve better results using oriented bounding boxes. If you want to go down that route, I would suggest using the EfficientDet model, because the PyTorch code that you'll find for it is quite easy to understand and modify. For example, I've taken https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch, and modified it to include a "thing-ness" logit, and this was pretty easy to do. Classic EfficientDet models only include logits (aka output neurons that get softmax-ed) for each class, and if any one of these class neurons is greater than 0.5, then it is considered "a thing". Anyway - that's digression, but my point is that I've thought about adding oriented box support to an EfficientDet model, and it didn't seem to be too hard, although I haven't actually done it. If I was to start now, I would probably go with https://github.com/rwightman/efficientdet-pytorch, since Ross Wightman's models are becoming a de-facto standard in the PyTorch world for all things image-related.
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operatorProject mention: [R] Involution: Inverting the Inherence of Convolution for Visual Recognition | reddit.com/r/MachineLearning | 2021-05-10
PDF Link | Landing Page | Read as web page on arXiv Vanity
A modern, web-based photo management server. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, face recognition, location awareness, color analysis and other ML algorithms.Project mention: (Pi 4B) What's a good program for a photo gallery ? | reddit.com/r/linux4noobs | 2022-01-10
Python object-detection related posts
Deepstack: Open-Source AI Server
2 projects | news.ycombinator.com | 19 Jan 2022
Equations for computing true positives and false positives when using object detection algorithms?
1 project | reddit.com/r/artificial | 13 Jan 2022
Why need to specify the output node of the IR when we use model optimizer to convert the YOLOv5 model ?
2 projects | reddit.com/r/deeplearning | 11 Jan 2022
YOLOv4/5 - Object Detection for Autonomous Driving - Datasets
2 projects | reddit.com/r/computervision | 5 Jan 2022
I like YOLOv5 but the code complexity is...
1 project | reddit.com/r/deeplearning | 2 Jan 2022
I want to create a pill counter using points instead of bounding boxes. What model should I train from?
7 projects | reddit.com/r/learnmachinelearning | 1 Jan 2022
Shared weights between different implementations
2 projects | reddit.com/r/learnmachinelearning | 1 Jan 2022
What are some of the best open-source object-detection projects in Python? This list will help you:
Are you hiring? Post a new remote job listing for free.