Franblueee/torchmil
Deep Multiple Instance Learning library for Pytorch
This library helps machine learning engineers and researchers build and train deep learning models for problems where data is grouped into 'bags' of instances rather than individual data points. You input datasets organized this way, like medical images composed of many small patches, and it outputs trained models capable of classifying or analyzing these 'bags'. This is useful for anyone working with specialized machine learning tasks that require Multiple Instance Learning.
Available on PyPI.
Use this if you are a machine learning practitioner working with PyTorch and need a robust framework to develop and apply Multiple Instance Learning models.
Not ideal if you are looking for a no-code solution or are unfamiliar with Python and deep learning frameworks like PyTorch.
Stars
74
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 03, 2026
Commits (30d)
0
Dependencies
9
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Franblueee/torchmil"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
nilearn/nilearn
Machine learning for NeuroImaging in Python
aramis-lab/clinica
Software platform for clinical neuroimaging studies
TissueImageAnalytics/tiatoolbox
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.
nipreps/mriqc
Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and...
nadeemlab/DeepLIIF
Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification...