2636 Repositories
Python image-segmentation-keras Libraries
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation (CVPR 2022)
CCAM (Unsupervised) Code repository for our paper "CCAM: Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localizati
Hyperbolic Image Segmentation, CVPR 2022
Hyperbolic Image Segmentation, CVPR 2022 This is the implementation of paper Hyperbolic Image Segmentation (CVPR 2022). Repository structure assets :
Maximum Spatial Perturbation for Image-to-Image Translation (Official Implementation)
MSPC for I2I This repository is by Yanwu Xu and contains the PyTorch source code to reproduce the experiments in our CVPR2022 paper Maximum Spatial Pe
The official codes of our CVPR2022 paper: A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift
TwoStageAlign The official codes of our CVPR2022 paper: A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift Pa
An example to implement a new backbone with OpenMMLab framework.
Backbone example on OpenMMLab framework English | 简体中文 Introduction This is an template repo about how to use OpenMMLab framework to develop a new bac
Library for converting from RGB / GrayScale image to base64 and back.
Library for converting RGB / Grayscale numpy images from to base64 and back. Installation pip install -U image_to_base_64 Conversion RGB to base 64 b
Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution
FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T
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
Official Implementation of HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation by Lukas Hoyer, Dengxin Dai, and Luc Van Gool [Arxiv] [Paper] Overview Unsup
[CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
Attention Helps CNN See Better: Hybrid Image Quality Assessment Network [CVPRW 2022] Code for Hybrid Image Quality Assessment Network [paper] [code] T
Classification models 1D Zoo - Keras and TF.Keras
Classification models 1D Zoo - Keras and TF.Keras This repository contains 1D variants of popular CNN models for classification like ResNets, DenseNet
code for paper"A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"
PyTorch implementation of UAGAN(U-net Attention Generative Adversarial Networks) This repository contains the source code for the paper "A High-precis
The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation"
SD-AANet The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation" [arxiv] Overview confi
Sound-guided Semantic Image Manipulation - Official Pytorch Code (CVPR 2022)
🔉 Sound-guided Semantic Image Manipulation (CVPR2022) Official Pytorch Implementation Sound-guided Semantic Image Manipulation IEEE/CVF Conference on
Optimizes image files by converting them to webp while also updating all references.
About Optimizes images by (re-)saving them as webp. For every file it replaced it automatically updates all references. Works on single files as well
Converts an image into funny, smaller amongus characters
SussyImage Converts an image into funny, smaller amongus characters Demo Mona Lisa | Lona Misa (Made up of AmongUs characters) API I've also added an
A python-image-classification web application project, written in Python and served through the Flask Microframework
A python-image-classification web application project, written in Python and served through the Flask Microframework. This Project implements the VGG16 covolutional neural network, through Keras and Tensorflow wrappers, to make predictions on uploaded images.
Implementation of the Hybrid Perception Block and Dual-Pruned Self-Attention block from the ITTR paper for Image to Image Translation using Transformers
ITTR - Pytorch Implementation of the Hybrid Perception Block (HPB) and Dual-Pruned Self-Attention (DPSA) block from the ITTR paper for Image to Image
Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Retrieval.
Targeted Trojan-Horse Attacks on Language-based Image Retrieval Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Re
Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow.
custom-cnn-fashion-mnist Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow. The following
A variational Bayesian method for similarity learning in non-rigid image registration (CVPR 2022)
A variational Bayesian method for similarity learning in non-rigid image registration We provide the source code and the trained models used in the re
Python scripts for performing road segemtnation and car detection using the HybridNets multitask model in ONNX.
ONNX-HybridNets-Multitask-Road-Detection Python scripts for performing road segemtnation and car detection using the HybridNets multitask model in ONN
Official implementation of Unfolded Deep Kernel Estimation for Blind Image Super-resolution.
Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima
This is an official implementation of the CVPR2022 paper "Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots".
Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit
Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"
On-the-Fly Adaptation Official Pytorch Code base for On-the-Fly Test-time Adaptation for Medical Image Segmentation Paper Introduction One major probl
Code for CVPR 2022 paper "SoftGroup for Instance Segmentation on 3D Point Clouds"
SoftGroup We provide code for reproducing results of the paper SoftGroup for 3D Instance Segmentation on Point Clouds (CVPR 2022) Author: Thang Vu, Ko
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
Using Unreliable Pseudo Labels Official PyTorch implementation of Semi-Supervised Semantic Segmentation Using Unreliable Pseudo Labels, CVPR 2022. Ple
Comparison-of-OCR (KerasOCR, PyTesseract,EasyOCR)
Optical Character Recognition OCR (Optical Character Recognition) is a technology that enables the conversion of document types such as scanned paper
Exploring the Dual-task Correlation for Pose Guided Person Image Generation
Dual-task Pose Transformer Network The source code for our paper "Exploring Dual-task Correlation for Pose Guided Person Image Generation“ (CVPR2022)
Image Lowpoly based on Centroid Voronoi Diagram via python-opencv and taichi
CVTLowpoly: Image Lowpoly via Centroid Voronoi Diagram Image Sharp Feature Extraction using Guide Filter's Local Linear Theory via opencv-python. The
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark Yong
TwitterBot-ImageCollector - Twitter bot that collects images from likes saves the image
TwitterBot-ImageCollector Bot de Twitter que recolecta imagenes a partir de los
S2s2net - Sentinel-2 Super-Resolution Segmentation Network
S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install
Example-custom-ml-block-keras - Custom Keras ML block example for Edge Impulse
Custom Keras ML block example for Edge Impulse This repository is an example on
Digitalizing-Prescription-Image - PIRDS - Prescription Image Recognition and Digitalizing System is a OCR make with Tensorflow
Digitalizing-Prescription-Image PIRDS - Prescription Image Recognition and Digit
Official code release for: EditGAN: High-Precision Semantic Image Editing
Official code release for: EditGAN: High-Precision Semantic Image Editing
Image generation API.
Image Generator API This is an api im working on Currently its just a test project Im trying to make custom readme images with your discord account pr
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation In this repo you can find the code of the Supervised Hybrid Audio Segmentatio
Transfer style api - An API to use with Tranfer Style App, where you can use two image and transfer the style
Transfer Style API It's an API to use with Tranfer Style App, where you can use
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers Authors: Jaemin Cho, Abhay Zala, and Mohit Bansal (
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentation"
Hyper-Convolution Networks for Biomedical Image Segmentation Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentatio
Using Opencv ,based on Augmental Reality(AR) and will show the feature matching of image and then by finding its matching
Using Opencv ,this project is based on Augmental Reality(AR) and will show the feature matching of image and then by finding its matching ,it will just mask that image . This project ,if used in cctv then it will detect black listed people if mentioned properly with their images.
Image2scan - a python program that can be applied on an image in order to get a scan of it back
image2scan Purpose image2scan is a python program that can be applied on an image in order to get a scan of it back. For this purpose, it searches for
OMLT: Optimization and Machine Learning Toolkit
OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.
A lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look At CoefficienTs)
Real-time Instance Segmentation and Lane Detection This is a lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look
Different steganography methods with examples and my own small image database
literally-the-most-useless-project [Different steganography methods with examples and my own small image database] This project currently contains thr
Image-to-image regression with uncertainty quantification in PyTorch
Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.
Learning Visual Words for Weakly-Supervised Semantic Segmentation
[IJCAI 2021] Learning Visual Words for Weakly-Supervised Semantic Segmentation Implementation of IJCAI 2021 paper Learning Visual Words for Weakly-Sup
Reading list for research topics in Masked Image Modeling
awesome-MIM Reading list for research topics in Masked Image Modeling(MIM). We list the most popular methods for MIM, if I missed something, please su
A framework for GPU based high-performance medical image processing and visualization
FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers Authors: Jaemin Cho, Abhay Zala, and Mohit Bansal (
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.
Official repository for GCR rerank, a GCN-based reranking method for both image and video re-ID
Official repository for GCR rerank, a GCN-based reranking method for both image and video re-ID
End-to-end image captioning with EfficientNet-b3 + LSTM with Attention
Image captioning End-to-end image captioning with EfficientNet-b3 + LSTM with Attention Model is seq2seq model. In the encoder pretrained EfficientNet
This project uses ViT to perform image classification tasks on DATA set CIFAR10.
Vision-Transformer-Multiprocess-DistributedDataParallel-Apex Introduction This project uses ViT to perform image classification tasks on DATA set CIFA
NeuroGen: activation optimized image synthesis for discovery neuroscience
NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target image;
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training (ISBI 2022)
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis Pretrained Models In this work, we created synthetic tissue
Generate waves art for an image
waves-art Generate waves art for an image. Requirements: OpenCV Numpy Example Usage python waves_art.py --image_path tests/test1.jpg --patch_size 15 T
Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset
SW-CV-ModelZoo Repo for my Tensorflow/Keras CV experiments. Mostly revolving around the Danbooru20xx dataset Framework: TF/Keras 2.7 Training SQLite D
Pytorch implementation of MaskGIT: Masked Generative Image Transformer
Pytorch implementation of MaskGIT: Masked Generative Image Transformer
Simple Python package to convert an image into a quantized image using a customizable palette
Simple Python package to convert an image into a quantized image using a customizable palette. Resulting image can be displayed by ePaper displays such as Waveshare displays.
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation By Qing Xu, Wenting Duan and Na He Requirements pytorch==1.1
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation This reposi
Image Data Augmentation in Keras
Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset.
Data Augmentation Using Keras and Python
Data-Augmentation-Using-Keras-and-Python Data augmentation is the process of increasing the number of training dataset. Keras library offers a simple
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection"
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py
Pytorch Implementation for Dilated Continuous Random Field
DilatedCRF Pytorch implementation for fully-learnable DilatedCRF. If you find my work helpful, please consider our paper: @article{Mo2022dilatedcrf,
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo
This repository contains the implementation of the paper Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans This repository contains the implementation of the pap
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions
Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr
Customers Segmentation with RFM Scores and K-means
Customer Segmentation with RFM Scores and K-means RFM Segmentation table: K-Means Clustering: Business Problem Rule-based customer segmentation machin
A transformer which can randomly augment VOC format dataset (both image and bbox) online.
VocAug It is difficult to find a script which can augment VOC-format dataset, especially the bbox. Or find a script needs complex requirements so it i
To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.
To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.
CT Based COVID 19 Diagnose by Image Processing and Deep Learning
This project proposed the deep learning and image processing method to undertake the diagnosis on 2D CT image and 3D CT volume.
Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.
Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.
FishNet: One Stage to Detect, Segmentation and Pose Estimation
FishNet FishNet: One Stage to Detect, Segmentation and Pose Estimation Introduction In this project, we combine target detection, instance segmentatio
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio
CCP dataset from Clothing Co-Parsing by Joint Image Segmentation and Labeling
Clothing Co-Parsing (CCP) Dataset Clothing Co-Parsing (CCP) dataset is a new clothing database including elaborately annotated clothing items. 2, 098
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
YOLOv7 - Framework Beyond Detection
🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
Weather Image Recognition - Python weather application using series of data
Weather Image Recognition - Python weather application using series of data
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Semantic Segmentation Suite in TensorFlow
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
Image Segmentation and Object Detection in Pytorch
Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report
This project aims at providing a concise, easy-to-use, modifiable reference implementation for semantic segmentation models using PyTorch.
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
Javascript image annotation tool based on image segmentation.
JS Segment Annotator Javascript image annotation tool based on image segmentation. Label image regions with mouse. Written in vanilla Javascript, with
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
Image Smoothing and Blurring Using OpenCV
Image-Smoothing-and-Blurring-Using-OpenCV This repository contains codes for performing image smoothing and blurring using OpenCV. There are different
Thresholding-and-masking-using-OpenCV - Image Thresholding is used for image segmentation
Image Thresholding is used for image segmentation. From a grayscale image, thresholding can be used to create binary images. In thresholding we pick a threshold T.
Simple Python script that lets you upload image/video to imgur
Pymgur 🐍 Simple Python script that lets you upload image/video to imgur! Usage 🔨 Git Clone this repository install the requirements (pip install -r
This project proposes a camera vision based cursor control system, using hand moment captured from a webcam through a landmarks of hand by using Mideapipe module
This project proposes a camera vision based cursor control system, using hand moment captured from a webcam through a landmarks of hand by using Mideapipe module