231 Repositories
Python train-CLIP Libraries
How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop
Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer
One line to host them all. Bootstrap your image search case in minutes.
One line to host them all. Bootstrap your image search case in minutes. Survey NOW gives the world access to customized neural image search in just on
Python package to generate image embeddings with CLIP without PyTorch/TensorFlow
imgbeddings A Python package to generate embedding vectors from images, using OpenAI's robust CLIP model via Hugging Face transformers. These image em
RuDOLPH: One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP
[Paper] [Хабр] [Model Card] [Colab] [Kaggle] RuDOLPH 🦌 🎄 ☃️ One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP Russian Diffusio
VQGAN+CLIP Colab Notebook with user-friendly interface.
VQGAN+CLIP and other image generation system VQGAN+CLIP Colab Notebook with user-friendly interface. Latest Notebook: Mse regulized zquantize Notebook
StorSeismic: An approach to pre-train a neural network to store seismic data features
StorSeismic: An approach to pre-train a neural network to store seismic data features This repository contains codes and resources to reproduce experi
Unified API to facilitate usage of pre-trained "perceptor" models, a la CLIP
mmc installation git clone https://github.com/dmarx/Multi-Modal-Comparators cd 'Multi-Modal-Comparators' pip install poetry poetry build pip install d
Language Models Can See: Plugging Visual Controls in Text Generation
Language Models Can See: Plugging Visual Controls in Text Generation Authors: Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lin
Official Pytorch implementation of the paper "MotionCLIP: Exposing Human Motion Generation to CLIP Space"
MotionCLIP Official Pytorch implementation of the paper "MotionCLIP: Exposing Human Motion Generation to CLIP Space". Please visit our webpage for mor
CLIP (Contrastive Language–Image Pre-training) for Italian
Italian CLIP CLIP (Radford et al., 2021) is a multimodal model that can learn to represent images and text jointly in the same space. In this project,
KoCLIP: Korean port of OpenAI CLIP, in Flax
KoCLIP This repository contains code for KoCLIP, a Korean port of OpenAI's CLIP. This project was conducted as part of Hugging Face's Flax/JAX communi
A Real-ESRGAN equipped Colab notebook for CLIP Guided Diffusion
#360Diffusion automatically upscales your CLIP Guided Diffusion outputs using Real-ESRGAN. Latest Update: Alpha 1.61 [Main Branch] - 01/11/22 Layout a
An ever-growing playground of notebooks showcasing CLIP's impressive zero-shot capabilities.
Playground for CLIP-like models Demo Colab Link GradCAM Visualization Naive Zero-shot Detection Smarter Zero-shot Detection Captcha Solver Changelog 2
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.
VQGAN-CLIP-GENERATOR Overview This is a package (with available notebook) for running VQGAN+CLIP locally, with a focus on ease of use, good documentat
In this tutorial, you will perform inference across 10 well-known pre-trained object detectors and fine-tune on a custom dataset. Design and train your own object detector.
Object Detection Object detection is a computer vision task for locating instances of predefined objects in images or videos. In this tutorial, you wi
CLIPfa: Connecting Farsi Text and Images
CLIPfa: Connecting Farsi Text and Images OpenAI released the paper Learning Transferable Visual Models From Natural Language Supervision in which they
PromptDet: Expand Your Detector Vocabulary with Uncurated Images
PromptDet: Expand Your Detector Vocabulary with Uncurated Images Paper Website Introduction The goal of this work is to establish a scalable pipeline
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP
CLIP-GEN [简体中文][English] 本项目在萤火二号集群上用 PyTorch 实现了论文 《CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP》。 CLIP-GEN 是一个 Language-F
[arXiv22] Disentangled Representation Learning for Text-Video Retrieval
Disentangled Representation Learning for Text-Video Retrieval This is a PyTorch implementation of the paper Disentangled Representation Learning for T
Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class.
CNNs fruits360 Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class. CNN on a pretrained model Build a CNN on a pretrained model, Res
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"
MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved
A python scripts that uses 3 different feature extraction methods such as SIFT, SURF and ORB to find a book in a video clip and project trailer of a movie based on that book, on to it.
A python scripts that uses 3 different feature extraction methods such as SIFT, SURF and ORB to find a book in a video clip and project trailer of a movie based on that book, on to it.
This is a modification of the OpenAI-CLIP repository of moein-shariatnia
This is a modification of the OpenAI-CLIP repository of moein-shariatnia
Application to help find best train itinerary, uses speech to text, has a spam filter to segregate invalid inputs, NLP and Pathfinding algos.
T-IAI-901-MSC2022 - GROUP 18 Gestion de projet Notre travail a été organisé et réparti dans un Trello. https://trello.com/b/X3s2fpPJ/ia-projet Install
A collection of Jupyter notebooks to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.
StyleGAN3 CLIP-based guidance StyleGAN3 + CLIP StyleGAN3 + inversion + CLIP This repo is a collection of Jupyter notebooks made to easily play with St
RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network trained to work with different pairs (images, texts).
RuCLIPtiny Zero-shot image classification model for Russian language RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network
This is an early in-development version of training CLIP models with hivemind.
A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look
This repo contains the code required to train the multivariate time-series Transformer.
Multi-Variate Time-Series Transformer This repo contains the code required to train the multivariate time-series Transformer. Download the data The No
Dicionario-git-github - Dictionary created to help train new users of Git and GitHub applications
Dicionário 📕 Dicionário criado com o objetivo de auxiliar no treinamento de nov
RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and rearranging captions and pictures. Unlike other versions of the model we use BERT for text encoder and SWIN transformer for image encoder.
ruCLIP-SB RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and re
Simple flask api. Countdown to next train for each station in the subway system.
Simple flask api. Countdown to next train for each station in the subway system.
Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses
Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss
NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models
NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,
A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret
This model involves Insurance bill prediction, which was subsequently deployed on Heroku PaaS
This repository contains code to train and render Mixture of Volumetric Primitives (MVP) models
Mixture of Volumetric Primitives -- Training and Evaluation This repository contains code to train and render Mixture of Volumetric Primitives (MVP) m
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs
CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair
Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET
Training COMET using seq2seq setting Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET. The codes are modified from run_summarizati
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code
sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ
Cereal box identification in store shelves using computer vision and a single train image per model.
Product Recognition on Store Shelves Description You can read the task description here. Report You can read and download our report here. Step A - Mu
Applying CLIP to Point Cloud Recognition.
PointCLIP: Point Cloud Understanding by CLIP This repository is an official implementation of the paper 'PointCLIP: Point Cloud Understanding by CLIP'
A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101
A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre
The aim of the game, as in the original one, is to find a specific image from a group of different images of a person's face
GUESS WHO Main Links: [Github] [App] Related Links: [CLIP] [Celeba] The aim of the game, as in the original one, is to find a specific image from a gr
Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters"
Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters" Pipeline of CLIP-Adapter CLIP-Adapter is a drop-in modul
Neural Cellular Automata + CLIP
🧠 Text-2-Cellular Automata Using Neural Cellular Automata + OpenAI CLIP (Work in progress) Examples Text Prompt: Cthulu is watching cthulu_is_watchin
Using OpenAI's CLIP to upscale and enhance images
CLIP Upscaler and Enhancer Using OpenAI's CLIP to upscale and enhance images Based on nshepperd's JAX CLIP Guided Diffusion v2.4 Sample Results Viewpo
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
CLIP2Video: Mastering Video-Text Retrieval via Image CLIP
CLIP2Video: Mastering Video-Text Retrieval via Image CLIP The implementation of paper CLIP2Video: Mastering Video-Text Retrieval via Image CLIP. CLIP2
Use CLIP to represent video for Retrieval Task
A Straightforward Framework For Video Retrieval Using CLIP This repository contains the basic code for feature extraction and replication of results.
Meta learning algorithms to train cross-lingual NLI (multi-task) models
Meta learning algorithms to train cross-lingual NLI (multi-task) models
This is a good project to train your logic game with python language
JO-KEN-PÔ!!! | Description | basic. I make this game only to train. This is a good project to train your logic game with python language. This game is
Files for a tutorial to train SegNet for road scenes using the CamVid dataset
SegNet and Bayesian SegNet Tutorial This repository contains all the files for you to complete the 'Getting Started with SegNet' and the 'Bayesian Seg
Project dự đoán giá cổ phiếu bằng thuật toán LSTM gồm: code train và code demo
Web predicts stock prices using Long - Short Term Memory algorithm Give me some start please!!! User interface image: Choose: DayBegin, DayEnd, Stock
This repository is a basic Machine Learning train & validation Template (Using PyTorch)
pytorch_ml_template This repository is a basic Machine Learning train & validation Template (Using PyTorch) TODO Markdown 사용법 Build Docker 사용법 Anacond
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals
Train Yolov4 using NBX-Jobs
yolov4-trainer-nbox Train Yolov4 using NBX-Jobs. Use the powerfull functionality available in nbox-SDK repo to train a tiny-Yolo v4 model on Pascal VO
Script and models for clustering LAION-400m CLIP embeddings.
clustering-laion400m Script and models for clustering LAION-400m CLIP embeddings. Models were fit on the first million or so image embeddings. A subje
Python package for Near Duplicate Video Detection (Perceptual Video Hashing) - Get a 64-bit comparable hash-value for any video.
The Python package for near duplicate video detection ⭐️ Introduction Videohash is a Python package for detecting near-duplicate videos (Perceptual Vi
RuDOLPH: One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP
[Paper] [Хабр] [Model Card] [Colab] [Kaggle] RuDOLPH 🦌 🎄 ☃️ One Hyper-Modal Tr
A Simulation Environment to train Robots in Large Realistic Interactive Scenes
iGibson: A Simulation Environment to train Robots in Large Realistic Interactive Scenes iGibson is a simulation environment providing fast visual rend
PASSL包含 SimCLR,MoCo,BYOL,CLIP等基于对比学习的图像自监督算法以及 Vision-Transformer,Swin-Transformer,BEiT,CVT,T2T,MLP_Mixer等视觉Transformer算法
PASSL Introduction PASSL is a Paddle based vision library for state-of-the-art Self-Supervised Learning research with PaddlePaddle. PASSL aims to acce
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
It is a simple library to speed up CLIP inference up to 3x (K80 GPU)
CLIP-ONNX It is a simple library to speed up CLIP inference up to 3x (K80 GPU) Usage Install clip-onnx module and requirements first. Use this trick !
Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.
Streamlit - Drawable Canvas Streamlit component which provides a sketching canvas using Fabric.js. Features Draw freely, lines, circles, boxes and pol
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.
Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
Learning to Self-Train for Semi-Supervised Few-Shot
Learning to Self-Train for Semi-Supervised Few-Shot Classification This repository contains the TensorFlow implementation for NeurIPS 2019 Paper "Lear
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.
CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we
OpenAI CLIP text encoders for multiple languages!
Multilingual-CLIP OpenAI CLIP text encoders for any language Colab Notebook · Pre-trained Models · Report Bug Overview OpenAI recently released the pa
EmoTag helps you train emotion detection model for Chinese audios
emoTag emoTag helps you train emotion detection model for Chinese audios. Environment pip install -r requirement.txt Data We used Emotional Speech Dat
PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.
ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab
VQGAN-CLIP-Video cat.mp4 policeman.mp4 schoolboy.mp4 forsenBOG.mp4
Train BPE with fastBPE, and load to Huggingface Tokenizer.
BPEer Train BPE with fastBPE, and load to Huggingface Tokenizer. Description The BPETrainer of Huggingface consumes a lot of memory when I am training
TerminalGV is a very simple client to display stats about your SNCF TGV/TER train in your terminal.
TerminalGV So I got bored in the train, TerminalGV is a very simple client to display stats about your SNCF TGV/TER train in your terminal. The "on-tr
This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees
Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe
Working demo of the Multi-class and Anomaly classification model using the CLIP feature space
👁️ Hindsight AI: Crime Classification With Clip About For Educational Purposes Only This is a recursive neural net trained to classify specific crime
Train emoji embeddings based on emoji descriptions.
emoji2vec This is my attempt to train, visualize and evaluate emoji embeddings as presented by Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts
t5-japanese Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts. The following is a list of models that
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.
Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.
A concise but complete implementation of CLIP with various experimental improvements from recent papers
x-clip (wip) A concise but complete implementation of CLIP with various experimental improvements from recent papers Install $ pip install x-clip Usag
A concise but complete implementation of CLIP with various experimental improvements from recent papers
x-clip (wip) A concise but complete implementation of CLIP with various experimental improvements from recent papers Install $ pip install x-clip Usag
Train custom VR face tracking parameters
Pal Buddy Guy: The anipal's best friend This is a small script to improve upon the tracking capabilities of the Vive Pro Eye and facial tracker. You c
Reproduction of Vision Transformer in Tensorflow2. Train from scratch and Finetune.
Vision Transformer(ViT) in Tensorflow2 Tensorflow2 implementation of the Vision Transformer(ViT). This repository is for An image is worth 16x16 words
A simple library that implements CLIP guided loss in PyTorch.
pytorch_clip_guided_loss: Pytorch implementation of the CLIP guided loss for Text-To-Image, Image-To-Image, or Image-To-Text generation. A simple libr
Train and use generative text models in a few lines of code.
blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa
Yas CRNN model training - Yet Another Genshin Impact Scanner
Yas-Train Yet Another Genshin Impact Scanner 又一个原神圣遗物导出器 介绍 该仓库为 Yas 的模型训练程序 相关资料 MobileNetV3 CRNN 使用 假设你会设置基本的pytorch环境。 生成数据集 python main.py gen 训练
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization
FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat
The repo contains the code to train and evaluate a system which extracts relations and explanations from dialogue.
The repo contains the code to train and evaluate a system which extracts relations and explanations from dialogue. How do I cite D-REX? For now, cite
Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition"
CLIPstyler Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" Environment Pytorch 1.7.1, Python 3.6 $ c
CLIP (Contrastive Language–Image Pre-training) trained on Indonesian data
CLIP-Indonesian CLIP (Radford et al., 2021) is a multimodal model that can connect images and text by training a vision encoder and a text encoder joi
Train neural network for semantic segmentation (deep lab V3) with pytorch in less then 50 lines of code
Train neural network for semantic segmentation (deep lab V3) with pytorch in 50 lines of code Train net semantic segmentation net using Trans10K datas
Contrastive Language-Image Pretraining
CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair
Train Dense Passage Retriever (DPR) with a single GPU
Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G
Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition"
CLIPstyler Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" Environment Pytorch 1.7.1, Python 3.6 $ c
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021
efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".
EMNLP 2021 paper "Pre-train or Annotate? Domain Adaptation with a Constrained Budget".
Pre-train or Annotate? Domain Adaptation with a Constrained Budget This repo contains code and data associated with EMNLP 2021 paper "Pre-train or Ann
Train the HRNet model on ImageNet
High-resolution networks (HRNets) for Image classification News [2021/01/20] Add some stronger ImageNet pretrained models, e.g., the HRNet_W48_C_ssld_
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators [Project Website] [Replicate.ai Project] StyleGAN-NADA: CLIP-Guided Domain Adaptation
This is the face keypoint train code of project face-detection-project
face-key-point-pytorch 1. Data structure The structure of landmarks_jpg is like below: |--landmarks_jpg |----AFW |------AFW_134212_1_0.jpg |------AFW_