Alessandro Guida's starred repositories
Transformers-Tutorials
This repository contains demos I made with the Transformers library by HuggingFace.
imbalanced-dataset-sampler
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
mil_pytorch
Multiple instance learning model implemented in pytorch
Segment-and-Track-Anything
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.
segment-anything-finetuner
Simple Finetuning Starter Code for Segment Anything
segment-anything
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.
PROSTATEx_masks
Lesion and prostate masks for the PROSTATEx training dataset, after a lesion-by-lesion quality check.
stylegan2-ada-pytorch-multiclass-labels
stylegan2-ada-pytorch-multiclass-labels
stylegan2-ada
StyleGAN2 with adaptive discriminator augmentation (ADA) - Official TensorFlow implementation
Image-Super-Resolution-via-Iterative-Refinement
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
code-server
VS Code in the browser
PerceptualSimilarity
LPIPS metric. pip install lpips
Jalali-Lab-Implementation-of-RAISR
Implementation of RAISR (Rapid and Accurate Image Super Resolution) algorithm in Python 3.x by Jalali Laboratory at UCLA. The implementation presented here achieved performance results that are comparable to that presented in Google's research paper (with less than ± 0.1 dB in PSNR). Just-in-time (JIT) compilation employing JIT numba is used to speed up the Python code. A very parallelized Python code employing multi-processing capabilities is used to speed up the testing process. The code has been tested on GNU/Linux and Mac OS X 10.13.2 platforms.
best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
statrethinking_winter2019
Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019
practical-nlp-code
Official Repository for Code associated with 'Practical Natural Language Processing' book by O'Reilly Media