Reverse Dependencies of torchvision
The following projects have a declared dependency on torchvision:
- bob.bio.face — Tools for running face recognition experiments
- bobotools — bobotools
- boilr — Basic framework for training models with PyTorch
- BoltRP — Torch-powered RQA
- boolean-question — Boolean question-answer prediction with AI
- boosting-cv-llm-sentiment — A Python library enhancing conversational AI with emotion detection, using computer vision and NLP. It tags emotions from facial expressions in real-time and integrates them with a Large Language Model for empathetic responses.
- borch — Probabilistic programming using pytorch.
- botorch — Bayesian Optimization in PyTorch
- boxmot — BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
- brainbox — Simplifying the life of a computational neuroscientist.
- BrainCog — BrainCog is an open source spiking neural network based brain-inspired cognitive intelligence engine for Brain-inspired Artificial Intelligence and brain simulation. More information on braincog can be found on its homepage http://www.brain-cog.network/
- brainmri-ps — Automatically classify Brain MRI series by pulse sequence types: FLAIR, T1C, T2, ADC, DWI, TOF and OTHER
- brainspy — A python package to support research on different nano-scale materials for creating hardware accelerators in the context of deep neural networks.
- brainways — Brainways
- brainways-reg-model — Brainways Registration Model
- breaching — Framework for Attacks against Privacy in Federated Learning
- breakhis-gradcam — Classification of the BreaKHis dataset with GradCAM support
- brevitas — Quantization-aware training in PyTorch
- BuilT — Easily build your trainer for DNNs.
- burdoc — Advanced PDF parsing for python
- byol-pytorch — Self-supervised contrastive learning made simple
- calapy — personal package
- caliber — Model-agnostic calibration and performance enhancement.
- calpit — no summary
- canary-sefi — Canary SEFI is a framework for evaluating the adversarial robustness of deep learning-based image recognition models.
- candlefl — A Python library for rapid prototyping, experimenting, and logging of federated learning using state-of-the-art models and datasets. Built using PyTorch and PyTorch Lightning.
- candlelight — no summary
- capreolus — A toolkit for end-to-end neural ad hoc retrieval
- Captcha-Impulse — hCaptcha bypass with yolov5
- captum — Model interpretability for PyTorch
- carla-recourse — A library for counterfactual recourse
- carlschader-ml-utils — A collection of utilities for machine learning projects
- cartwright — A recurrent neural network paired with heuristic methods that automatically infer geospatial, temporal and feature columns
- carvekit — Open-Source background removal framework
- carvekit-colab — Open-Source background removal framework
- cat-dog-classify-pytorch-test-gp — Deep Learning Model to classify Cats and Dogs usinbg PyTorch
- catalyst — Catalyst. Accelerated deep learning R&D with PyTorch.
- catalyst-pdm — Catalyst fork compatible with PDM
- catalyst-rl — Catalyst.RL. PyTorch framework for RL research.
- catchem-alpha-zero — CatchemAlphaZero: AI techniques for solving games
- catchMinor — model library for imbalanced-learning & anomaly detection in tabular, time series, graph data
- CCTorch — no summary
- cdisco — Concept discovery with Singular Value Decomposition
- ceevee — Python library for various computer vision problems with a focus on easy usage
- CEFR-Classifier-French — A French text classification package based on CEFR levels.
- CEFT-Classifier-French — A French text classification package.
- celldetection — Cell Detection with PyTorch.
- cellmap-models — Repository of model architectures and network weights used for CellMap segmentations.
- cellmaps-image-embedding — A tool to generate embeddings from HPA IF images
- cellmaps-vnn — Python Boilerplate contains all the boilerplate you need to create a Python package with command line
- cellshape — 3D shape analysis using deep learning
- cellshape-cloud — 3D cell shape analysis using geometric deep learning on point clouds
- cellshape-cluster — 3D shape analysis using deep learning
- cellshape-helper — 3D shape analysis using deep learning
- cellshape-voxel — 3D shape analysis using deep learning
- CellSNAP — A package for enhancing single-cell population delineation by integrating cross-domain information.
- cesped — Code utilities for the CESPED (Cryo-EM Supervised Pose Estimation Dataset) benchmark
- cfdonnx — Converting ML-CFD models to ONNX
- challenge.uccs — Source code for running the baseline and evaluation of the third UCCS face recognition challenge
- change-analyzer — Change analyzer
- change-detection-pytorch — Change detection models with pre-trained backbones. Inspired by segmentation_models.pytorch.
- changeos — ChangeOS SDK
- chariot-transforms — image processing transforms for Chariot
- charmory — Adversarial Robustness Evaluation Library
- chat-rag — no summary
- ChemIC-ml — Chemical images classification project. Program for training the neural network model and web service for classification images
- ChexpertClassifier — CheXpert Classification with EfficientNet B3
- chicken-coop — An environment for reproducing dominance hierarchies in RL agents
- chop-pytorch — Continuous and constrained optimization with PyTorch
- ciliaseg — no summary
- circuit-rbm — Train a RKM
- cjm-diffusers-utils — Some utility functions I frequently use with 🤗 diffusers.
- cjm-pytorch-utils — Some utility functions for working with PyTorch.
- cjm-torchvision-tfms — Some custom Torchvision tranforms.
- cjm-yolox-pytorch — A PyTorch implementation of the YOLOX object detection model based on the mmdetection implementation.
- classiq — Classiq's Python SDK for quantum computing
- classitransformers — An abstract library for implementing text classification tasks based on various transformers based language models
- classtree — A toolkit for hierarchical classification
- classy-vision — An end-to-end PyTorch framework for image and video classification.
- clean-fid — FID calculation in PyTorch with proper image resizing and quantization steps
- cleanocr — Automatically denoise degraded document images to improve ocr engine
- cleanvision — Find issues in image datasets
- cleverhans — no summary
- clinicadl — Framework for the reproducible processing of neuroimaging data with deep learning methods
- clip-anytorch — # CLIP
- clip-bbox — Python library for detecting image objects with natural language text labels
- clip-benchmark — CLIP-like models benchmarks on various datasets
- clip-by-openai — no summary
- clip-ea — no summary
- clip-interrogator — Generate a prompt from an image
- clip-ods — This lib is about a simple add-on over CLIP by OpenAI for Unsupervised Object Detection (Zeroshot). You can search bounding boxes of objects using NATURAL LANGUAGE UNDERSTANDING - no classes, only text.
- clip-openai — CLIP package of OpenAI
- clip-retrieval — Easily computing clip embeddings and building a clip retrieval system with them
- clip-score — Package for calculating Clip Score using PyTorch
- clip-text-decoder — Generate text captions for images from their CLIP embeddings.
- clip-video-encode — Easily compute clip embeddings from video frames
- clip2classdist — A Python script that analyzes image classes using OpenAI CLIP model
- clipbit — Generate concise meaningful summaries YouTube videos
- clipq — Paper - Pytorch
- cls-trainer-pytorch — General neural network classification trainer compatibile with PyTorch, grid search regime