image-crop-analysis VS SUBLIME

Compare image-crop-analysis vs SUBLIME and see what are their differences.

image-crop-analysis

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency (by twitter-research)

SUBLIME

Semantically Understanding Bias with LIME. Using the LIME-RS Algorithm to understand bias in recommender systems. (by FurkanToprak)
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image-crop-analysis SUBLIME
2 1
249 3
0.8% -
0.0 10.0
over 2 years ago over 2 years ago
Jupyter Notebook Jupyter Notebook
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.

image-crop-analysis

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

SUBLIME

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

What are some alternatives?

When comparing image-crop-analysis and SUBLIME you can also consider the following projects:

vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

qt-dab - Qt-DAB, a general software DAB (DAB+) decoder with a (slight) focus on showing the signal

Face-Mask-Detection - Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras

engineering-management - A collection of inspiring resources related to engineering management and tech leadership

oemer - End-to-end Optical Music Recognition (OMR) system. Transcribe phone-taken music sheet image into MusicXML, which can be edited and converted to MIDI.

interpret - Fit interpretable models. Explain blackbox machine learning.

neural-style-transfer - :paintbrush: This repository contains, well-structured Python library and runnable fully prepared Python notebook of the "Neural Style Transfer" algorithm

shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Neural-Style-Transfer - Pytorch implementation of Nueral Style transfer

AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

computervision-recipes - Best Practices, code samples, and documentation for Computer Vision.

CWOX - A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.