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Stars gained: From May 9, 2026 to Nov 13, 2026, each from zeroStars gainedFrom May 9, 2026 to Nov 13, 2026, each from zero020May 9Nov 13, 2026google-research-datasets/Objectrondragen1860/TensorFlow-2.x-Tutorials
Stars: The star count at the end of each dayStarsThe star count at the end of each day4K6KMay 9Nov 13, 2026google-research-datasets/Objectrondragen1860/TensorFlow-2.x-Tutorials

Facts

Fact google-research-datasets/Objectron

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

dragen1860/TensorFlow-2.x-Tutorials

TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码,实战教程。

Stars 2,3626,344
Net stars, last 30 days +5+6
Largest star day +3 on Jul 18, 2026+2 on Sep 16, 2026
Milestone reached in the record NoneNone
Forks 2682,172
Language Jupyter NotebookJupyter Notebook
License Other licenseNo license
Created Oct 19, 2020Jan 30, 2019
Last push Mar 6, 2026Sep 23, 2020
Archived NoNo
Health facts: Maintenance 1 of 4 checks (2 without data)1 of 4 checks (2 without data)
Health facts: Releases 1 of 3 checks (1 without data)0 of 3 checks (2 without data)
Health facts: Security practice 0 of 1 check (1 without data)0 of 1 check (1 without data)
Health facts: Community files 1 of 3 checks (2 without data)0 of 3 checks (2 without data)
Commits, last 13 weeks No dataNo data
Weeks with commits, last 52 No dataNo data
In the Repository Index since Nov 11, 2026Nov 10, 2026

Topics that all of them have on the Repository Host: deep-learning, computer-vision, machine-learning, tensorflow, neural-network. The facts come from the Repository Host and from the Star History that AwesomeRepos records. A shared topic does not mean that one repository can replace another. Each Health Facts row is one dimension alone. AwesomeRepos does not add them into one score. How each check is defined

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