ScanRefer VS AgML

Compare ScanRefer vs AgML and see what are their differences.

AgML

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations. (by Project-AgML)
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ScanRefer AgML
1 1
214 155
- 5.2%
0.0 7.5
about 1 year ago 6 days ago
Python Python
GNU General Public License v3.0 or later Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ScanRefer

Posts with mentions or reviews of ScanRefer. We have used some of these posts to build our list of alternatives and similar projects.

AgML

Posts with mentions or reviews of AgML. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing ScanRefer and AgML you can also consider the following projects:

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

gluon-cv - Gluon CV Toolkit

3DDFA - The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]

PTT - Official PyTorch Implementation for "PTT: Point-Track-Transformer Module for 3D Single Object Trackingin Point Clouds"

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

Entity - EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.

PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format