[D] Data Annotation Done by Machine Learning/AI?

• Grounded-Segment-Anything

  11 13,615 8.0 Jupyter Notebook

  Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

  

There are several AI models which aim to speed up labeling (like the recently released SAM). You may be interested in Grounded-SAM which is pretty much automated. https://github.com/IDEA-Research/Grounded-Segment-Anything But it may not perform well on specific domains.

• CLIP

  104 22,472 1.2 Jupyter Notebook

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• segment-anything

  56 44,293 0.0 Jupyter Notebook

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  

• GroundingDINO

  5 5,075 6.3 Python

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

  

Suggest a related project