Jupyter Notebook object-detection

Open-source Jupyter Notebook projects categorized as object-detection

Top 23 Jupyter Notebook object-detection Projects

  • automl

    Google Brain AutoML

    Project mention: Slowdown / normalization on the Front Lines | /r/singularity | 2023-05-30
  • YOLOv6

    YOLOv6: a single-stage object detection framework dedicated to industrial applications.

    Project mention: I want to make a Class monitoring system. is it possible in the conditions I'm in ?? | /r/computervision | 2022-12-08

    Some resources to get you started...https://towardsdatascience.com/object-detection-with-10-lines-of-code-d6cb4d86f606https://github.com/OlafenwaMoses/ImageAIhttps://towardsdatascience.com/yolo-object-detection-with-opencv-and-python-21e50ac599e9https://github.com/meituan/YOLOv6

  • Mergify

    Updating dependencies is time-consuming.. Solutions like Dependabot or Renovate update but don't merge dependencies. You need to do it manually while it could be fully automated! Add a Merge Queue to your workflow and stop caring about PR management & merging. Try Mergify for free.

  • Yet-Another-EfficientDet-Pytorch

    The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

  • simple-faster-rcnn-pytorch

    A simplified implemention of Faster R-CNN that replicate performance from origin paper

  • super-gradients

    Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

    Project mention: FLaNK Stack for 15 May 2023 | dev.to | 2023-05-15
  • notebooks

    Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM. (by roboflow)

    Project mention: Roboflow Notebooks: 30+ tutorials on using SOTA models and vision techniques | /r/computervision | 2023-08-31

    We (the Roboflow open source team) actively write open source Google Colab notebooks showing how to use new SOTA models. Our library covers SAM, CLIP, Detectron2, YOLOv8, RTMDet, DINOv2, and more. These notebooks helped me cross the chasm from "how do I use X model?" to being able to both write and understand inference code.

  • OwnPhotos

    Self hosted alternative to Google Photos

    Project mention: [Self Hosted] F * CK Google, voici quelques alternatives auto-hébergées. | /r/enfrancais | 2023-05-05

    * ~~ Ownphoto's ~~ * librephotos > Google Photo's

  • InfluxDB

    Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.

  • yolov3-tf2

    YoloV3 Implemented in Tensorflow 2.0

  • saliency

    Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).

    Project mention: [D] Is the math in Integrated gradients (4K citations) wrong? | /r/MachineLearning | 2023-05-05

    Found relevant code at https://github.com/PAIR-code/saliency + all code implementations here

  • pix2seq

    Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion) (by google-research)

    Project mention: Google released the source code of Pix2Seq: Object detection as a language modeling task | /r/machinelearningnews | 2022-11-26
  • TrainYourOwnYOLO

    Train a state-of-the-art yolov3 object detector from scratch!

  • TACO

    🌮 Trash Annotations in Context Dataset Toolkit (by pedropro)


    LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

  • maxvit

    [ECCV 2022] Official repository for "MaxViT: Multi-Axis Vision Transformer". SOTA foundation models for classification, detection, segmentation, image quality, and generative modeling...

  • sport

    Examples of Computer Vision usage in sports ⚽🏃

    Project mention: [OC] Counting People in the Zones with YOLOv8, OpenCV, and Supervision | /r/dataisbeautiful | 2023-02-21

    I actually have a project where I did exactly that: https://github.com/SkalskiP/sport. Maybe I'll upload it here next week ;)

  • SipMask

    SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation (ECCV2020)

  • roboflow-100-benchmark

    Code for replicating Roboflow 100 benchmark results and programmatically downloading benchmark datasets

    Project mention: AI That Teaches Other AI | news.ycombinator.com | 2023-07-20

    > Their SKILL tool involves a set of algorithms that make the process go much faster, they said, because the agents learn at the same time in parallel. Their research showed if 102 agents each learn one task and then share, the amount of time needed is reduced by a factor of 101.5 after accounting for the necessary communications and knowledge consolidation among agents.

    This is a really interesting idea. It's like the reverse of knowledge distillation (which I've been thinking about a lot[1]) where you have one giant model that knows a lot about a lot & you use that model to train smaller, faster models that know a lot about a little.

    Instead, you if you could train a lot of models that know a lot about a little (which is a lot less computationally intensive because the problem space is so confined) and combine them into a generalized model, that'd be hugely beneficial.

    Unfortunately, after a bit of digging into the paper & Github repo[2], this doesn't seem to be what's happening at all.

    > The code will learn 102 small and separte heads(either a linear head or a linear head with a task bias) for each tasks respectively in order. This step can be parallized on multiple GPUS with one task per GPU. The heads will be saved in the weight folder. After that, the code will learn a task mapper(Either using GMMC or Mahalanobis) to distinguish image task-wisely. Then, all images will be evaluated in the same time without a task label.

    So the knowledge isn't being combined (and the agents aren't learning from each other) into a generalized model. They're just training a bunch of independent models for specific tasks & adding a model-selection step that maps an image to the most relevant "expert". My guess is you could do the same thing using CLIP vectors as the routing method to supervised models trained on specific datasets (we found that datasets largely live in distinct regions of CLIP-space[3]).

    [1] https://github.com/autodistill/autodistill

    [2] https://github.com/gyhandy/Shared-Knowledge-Lifelong-Learnin...

    [3] https://www.rf100.org

  • HugsVision

    HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

  • fashionpedia-api

    Python API for Fashionpedia Dataset

  • auto_annotate

    Labeling is boring. Use this tool to speed up your next object detection project!

    Project mention: Labeling is boring. Use this tool to speed up your next object detection project! | /r/computervision | 2023-04-24
  • fasterrcnn-pytorch-training-pipeline

    PyTorch Faster R-CNN Object Detection on Custom Dataset

    Project mention: A simple library to train more than 20 Faster RCNN models using PyTorch (including ViTDet) | /r/deeplearning | 2023-06-07

    Distance Detector (People) with Yolov7

    Project mention: November 28, 2022 FLiP Stack Weekly | dev.to | 2022-12-19
  • vision-camera-realtime-object-detection

    VisionCamera Frame Processor Plugin to detect objects using TensorFlow Lite Task Vision

    Project mention: This Week In React-Native #137: Expo Code Elimination, Monorepo, Hermes, Chain React, EAS, Skia, Expo Router, VisionCamera, React-Native-Graph | /r/reactnative | 2023-03-09

    📦 VisionCamera Realtime Object Detection with TensorFlow Lite - demo

  • SonarQube

    Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.

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 2023-08-31.

Jupyter Notebook object-detection related posts


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

Project Stars
1 automl 6,000
2 YOLOv6 5,193
3 Yet-Another-EfficientDet-Pytorch 5,140
4 simple-faster-rcnn-pytorch 3,812
5 super-gradients 3,326
6 notebooks 3,120
7 OwnPhotos 2,735
8 yolov3-tf2 2,500
9 saliency 902
10 pix2seq 717
11 TrainYourOwnYOLO 633
12 TACO 516
13 LLVIP 503
14 maxvit 382
15 sport 367
16 SipMask 330
17 roboflow-100-benchmark 195
18 HugsVision 183
19 fashionpedia-api 130
20 auto_annotate 124
21 fasterrcnn-pytorch-training-pipeline 120
23 vision-camera-realtime-object-detection 80
Static code analysis for 29 languages.
Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.