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. Learn more →
Top 23 Jupyter Notebook object-detection Projects
-
-
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.
-
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 | 2023-08-31We (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.
-
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.
-
-
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 | 2023-05-05Found 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 -
-
-
-
maxvit
[ECCV 2022] Official repository for "MaxViT: Multi-Axis Vision Transformer". SOTA foundation models for classification, detection, segmentation, image quality, and generative modeling...
-
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
> 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...
-
-
-
Project mention: Labeling is boring. Use this tool to speed up your next object detection project! | /r/computervision | 2023-04-24
-
Project mention: A simple library to train more than 20 Faster RCNN models using PyTorch (including ViTDet) | /r/deeplearning | 2023-06-07
-
-
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.
Jupyter Notebook object-detection related posts
- Exploring the relationships between deprivation and litter on the streets of Glasgow
- Framework for machine learning?
- Mini PC for AI
- What are some USB devices worth using in a Home Lab Environment?
- Is a PCIe x1 enough for light ML tasks
- A simple library to train more than 20 Faster RCNN models using PyTorch (including ViTDet)
- Looking for a Mini PC for Home Assistant and Frigate.
-
A note from our sponsor - InfluxDB
www.influxdata.com | 29 Sep 2023
Index
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 |
22 | YOLOV7-OBJECT-COUNTER-V1.2 | 82 |
23 | vision-camera-realtime-object-detection | 80 |