Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual diagnostic tools called “Visualizers” that extend the scikit-learn API to allow human steering of the model selection process. In a nutshell, Yellowbrick combines scikit-learn with matplotlib in the best tradition of the scikit-learn documentation, but to produce visualizations for your machine learning workflow! For complete documentation on the Yellowbrick API, a gallery of available visualizers, the contributor’s guide, tutorials […]

NudeNet NudeNet: Neural Nets for Nudity Classification, Detection and selective censoring. Classifier classes: class name Description safe Image/Video is not sexually explicit unsafe Image/Video is sexually explicit Default Detector classes: class name Description EXPOSED_ANUS Exposed Anus; Any gender EXPOSED_ARMPITS Exposed Armpits; Any gender COVERED_BELLY Provocative, but covered Belly; Any gender EXPOSED_BELLY Exposed Belly; Any gender COVERED_BUTTOCKS Provocative, but covered Buttocks; Any gender EXPOSED_BUTTOCKS Exposed Buttocks; Any gender FACE_F Female Face FACE_M Male Face COVERED_FEET Covered Feet; Any gender EXPOSED_FEET Exposed […]

Polygon-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable polygon prediction boxes. Section I. Description The codes are based on Ultralytics/yolov5, and several functions are added and modified to enable polygon prediction boxes. The modifications compared with Ultralytics/yolov5 and their brief descriptions are summarized below: data/polygon_ucas.yaml : Exemplar UCAS-AOD dataset to test the effects of polygon boxes data/images/UCAS-AOD : For the inference of polygon-yolov5s-ucas.pt models/common.py :3.1. class Polygon_NMS : Non-Maximum Suppression (NMS) module for Polygon Boxes3.2. class Polygon_AutoShape […]

spacy-huggingface-hub This package provides a CLI command for uploading any trained spaCy pipeline packaged with spacy package to the Hugging Face Hub. It auto-generates all meta information for you, uploads a pretty README (requires spaCy v3.1+) and handles version control under the hood. About the Hugging Face Hub The Hugging Face Hub hosts Git-based repositories which are storage spaces that can contain all your files. These repositories have multiple advantages: versioning (commit history and diffs), branches, useful metadata about their […]

TumorInsight TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture. It aims to detect and classify the brain tumours from MRI scans. The detection is done using Image Processing algorithms and classification using Deep learning techniques.The model is also deployed as a web application using Flask framework. Download trained model from here. def main() text = “Hello World!” return text if __name__ == ‘__main__’: text = main() print(text) Lorem ipsum dolor sit amet, consectetur adipiscing elit. […]

Stable Baselines3 Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around which new ideas can be added, and as a tool for comparing a […]

VQGAN-CLIP A repo for running VQGAN+CLIP locally. This started out as a Katherine Crowson VQGAN+CLIP derived Google colab notebook. Some example images: Environment: Tested on Ubuntu 20.04 GPU: Nvidia RTX 3090 Typical VRAM requirements: 24 GB for a 900×900 image 10 GB for a 512×512 image 8 GB for a 380×380 image Still a work in progress – I’ve not actually tested everything yet 🙂 Example set up using Anaconda to create a virtual Python environment with the prerequisites: conda […]

MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. The constraints are defined as upper bounds on sub-objective loss function. MooGBT uses a Augmented Lagrangian(AL) based constrained optimization framework with Gradient Boosted Trees, to optimize for multiple objectives. With AL, we introduce dual variables in Boosting. The dual variables are iteratively optimized and fit within the Boosting iterations. The Boosting objective function is […]

Stylized Neural Painting Official PyTorch implementation of the preprint paper “Stylized Neural Painting”, accepted to CVPR 2021.We propose an image-to-painting translation method that generates vivid and realistic painting artworks with controllable styles. Different from previous image-to-image translation methods that formulate the translation as pixel-wise prediction, we deal with such an artistic creation process in a vectorized environment and produce a sequence of physically meaningful stroke parameters that can be further used for rendering. Since a typical vector render is not […]