Python object-detection

Open-source Python projects categorized as object-detection
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Topics: Deep Learning Computer Vision Pytorch Machine Learning Python
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Top 23 Python object-detection Projects

  • yolov5

    YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

    • Project mention: จำแนกสายพันธ์ุหมากับแมวง่ายๆด้วยYoLoV5 | dev.to | 2024-04-15

    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

  • mmdetection

    OpenMMLab Detection Toolbox and Benchmark

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    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • Mask_RCNN

    Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

    • Project mention: Intuituvely Understanding Harris Corner Detector | news.ycombinator.com | 2023-09-11

    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.

  • ultralytics

    NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

    • Project mention: The CEO of Ultralytics (yolov8) using LLMs to engage with commenters on GitHub | news.ycombinator.com | 2024-02-12

    Yep, I noticed this a while ago. It posts easily identifiable ChatGPT responses. It also posts garbage wrong answers which makes it worse than useless. Totally disrespectful to the userbase.

    https://github.com/ultralytics/ultralytics/issues/5748#issue...

  • frigate

    NVR with realtime local object detection for IP cameras

    • Project mention: Multimillion-dollar L.A. heist was seamless, sophisticated, stealthy | news.ycombinator.com | 2024-04-10

  • supervision

    We write your reusable computer vision tools. 💜

    • Project mention: Supervision: Reusable Computer Vision | news.ycombinator.com | 2024-03-24

    You can always slice the images into smaller ones, run detection on each tile, and combine results. Supervision has a utility for this - https://supervision.roboflow.com/latest/detection/tools/infe..., but it only works with detections. You can get a much more accurate result this way. Here is some side-by-side comparison: https://github.com/roboflow/supervision/releases/tag/0.14.0.

  • albumentations

    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/2078-2489/11/2/125

    • Project mention: Augment specific classes? | /r/computervision | 2023-12-06

    You can use albumentations if you are comfortable with using open source libraries https://github.com/albumentations-team/albumentations

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  • Swin-Transformer

    This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

    • Project mention: Samsung expected to report 80% profit plunge as losses mount at chip business | news.ycombinator.com | 2023-10-10

    > there is really nothing that "normal" AI requires that is bound to CUDA. pyTorch and Tensorflow are backend agnostic (ideally...).

    There are a lot of optimizations that CUDA has that are nowhere near supported in other software or even hardware. Custom cuda kernels also aren't as rare as one might think, they will often just be hidden unless you're looking at libraries. Our more well known example is going to be StyleGAN[0] but it isn't uncommon to see elsewhere, even in research code. Swin even has a cuda kernel[1]. Or find torch here[1] (which github reports that 4% of the code is cuda (and 42% C++ and 2% C)). These things are everywhere. I don't think pytorch and tensorflow could ever be agnostic, there will always be a difference just because you have to spend resources differently (developing kernels is time resource). We can draw evidence by looking at Intel MKL, which is still better than open source libraries and has been so for a long time.

    I really do want AMD to compete in this space. I'd even love a third player like Intel. We really do need competition here, but it would be naive to think that there's going to be a quick catchup here. AMD has a lot of work to do and posting a few bounties and starting a company (idk, called "micro grad"?) isn't going to solve the problem anytime soon.

    And fwiw, I'm willing to bet that most AI companies would rather run in house servers than from cloud service providers. The truth is that right now just publishing is extremely correlated to compute infrastructure (doesn't need to be but with all the noise we've just said "fuck the poor" because rejecting is easy) and anyone building products has costly infrastructure.

    [0] https://github.com/NVlabs/stylegan2-ada-pytorch/blob/d72cc7d...

    [1] https://github.com/microsoft/Swin-Transformer/blob/2cb103f2d...

    [2] https://github.com/pytorch/pytorch/tree/main/aten/src

  • PaddleDetection

    Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

  • yolov3

    YOLOv3 in PyTorch > ONNX > CoreML > TFLite

  • pytorch-grad-cam

    Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

    • Project mention: Exploring GradCam and More with FiftyOne | dev.to | 2024-02-13

    For the two examples we will be looking at, we will be using pytorch_grad_cam, an incredible open source package that makes working with GradCam very easy. There are excellent other tutorials to check out on the repo as well.

  • YOLOX

    YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

  • ImageAI

    A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

    • Project mention: Photo gallery frontend with encryption and search | /r/selfhosted | 2023-11-27

    Hi. I want to implement an image server similar to Photoprism using ImageAI to tag images based on objects and context. However I don't want to spend to much time working on the frontend, at first I were thinking about using Danbooru and use Flexbooru or the web interface on my phone. But it doesn't have any encryption or password protection (since the purpose of it is to be used as a public image board).

  • TensorLayer

    Deep Learning and Reinforcement Learning Library for Scientists and Engineers

  • autogluon

    AutoGluon: Fast and Accurate ML in 3 Lines of Code

    • Project mention: pip install remyxai - easiest way to create custom vision models | /r/computervision | 2023-04-25

    This seems not very convincing. There are other popular frameworks that provide AutoML with existing datasets (eg https://github.com/autogluon/autogluon)

  • darkflow

    Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

  • gluon-cv

    Gluon CV Toolkit

  • GroundingDINO

    Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

    • Project mention: Autodistill: A new way to create CV models | /r/developersIndia | 2023-09-30

    Some of the foundation/base models include: * GroundedSAM (Segment Anything Model) * DETIC * GroundingDINO

  • mmdetection3d

    OpenMMLab's next-generation platform for general 3D object detection.

    • Project mention: What's the best model to get monocular 3d angle info | /r/deeplearning | 2023-06-28

    There are bunch of methods in this codebase, check it out. https://github.com/open-mmlab/mmdetection3d

  • layout-parser

    A Unified Toolkit for Deep Learning Based Document Image Analysis

  • sahi

    Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

    • Project mention: Small-Object Detection using YOLOv8 | /r/computervision | 2023-08-15

    Hi All, I am trying to detect defects in the images using YOLOv8where some of the classes (defectType1, defectType2) have very small bounding boxes and some of them have large bounding boxes associated with the, (defectType3, defectType4). Also, real-time operation is desired (at least 5Hz on Jetson Xavier) What I have done till now: I am primarily trying to use the SAHI technique (Slicing Aided Hyper Inference)

  • AdelaiDet

    AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

  • catalyst

    Accelerated deep learning R&D (by catalyst-team)

    • Project mention: Instance segmentation of small objects in grainy drone imagery | /r/computervision | 2023-12-09

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2024-04-15.

Python object-detection related posts

Index

What are some of the best open-source object-detection projects in Python? This list will help you:

Project Stars
1 yolov5 46,738
2 mmdetection 27,658
3 Mask_RCNN 24,119
4 ultralytics 22,289
5 frigate 14,547
6 supervision 13,921
7 albumentations 13,362
8 Swin-Transformer 12,879
9 PaddleDetection 12,008
10 yolov3 9,981
11 pytorch-grad-cam 9,351
12 YOLOX 9,005
13 ImageAI 8,383
14 TensorLayer 7,275
15 autogluon 7,050
16 darkflow 6,131
17 gluon-cv 5,751
18 GroundingDINO 4,916
19 mmdetection3d 4,758
20 layout-parser 4,438
21 sahi 3,534
22 AdelaiDet 3,326
23 catalyst 3,221

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