A Toolbox for Image Feature Matching and Evaluations In this repository, we provide easy interfaces for several exisiting SotA methods to match image feature correspondences between image pairs.We provide scripts to evaluate their predicted correspondences on common benchmarks for the tasks of image matching, homography estimation and visual localization. Notice This repository is expected to be actively maintained (at least before I graduate🤣🤣) and gradually (slowly) grow for new features of interest. Suggestions regarding how to improve this repo, such […]

py-nudec py-nudec (python nude detector) is a microservice, which scans all the images and videos from the multipart/form-data request payload and sends a response with a boolean value which indicates if all content has passed the checks. This service uses NudeNet created by notAI-tech Configuration Initialize a virtual environment using virtualenv and start it # Install virtualenv pip3 install virtualenv # Create a virtual environment py -m virtualenv venv # Activate virtual environment source venv/scripts/activate Install all required packages pip3 […]

Object-Shadow-Generation-Dataset-DESOBA Object Shadow Generation is to deal with the shadow inconsistency between the foreground object and the background in a composite image, that is, generating shadow for the foreground object according to background information, to make the composite image more realistic. Our dataset DESOBA is a synthesized dataset for Object Shadow Generation. We build our dataset on the basis of Shadow-OBject Association dataset SOBA, which collects real-world images in complex scenes and provides annotated masks for object-shadow pairs. Based on […]

Learning to See by Looking at Noise In this work, we investigate a suite of image generation models that produce images from simple random processes. These are then used as training data for a visual representation learner with a contrastive loss. We study two types of noise processes, statistical image models and deep generative models under different random initializations. Requirements This version of code has been tested with Python 3.7.7 and pytorch 1.6.0. Other versions of pytorch are likely to […]

WADs Out For [The] Ladies Simple Python / ImageMagick script to package images into WAD3s for use as GoldSrc textures. Development mostly focused on Linux, where a native WAD file creator is MIA. wofl input1 [input2 …] output input1 [input2 …] are the input images output is the output WAD filename Example $ ./wofl.py pictures/file.jpg my_wad.wad $ echo $? 0 # success ImageMagick (its executables have to be in the system PATH) GitHub https://github.com/Schlufi/wofl    

BeeRef BeeRef lets you quickly arrange your reference images and view them while you create. Its minimal interface is designed not to get in the way of your creative process. Installation via Python & pip At the moment, you need to have a working Python 3 environment to install BeeRef. Run the following command to install the development version: pip install git+https://github.com/rbreu/beeref.git Then run beeref or beeref filename.bee. If there are issues starting the application, run it with the environment […]

CoSMo.pytorch Official Implementation of CoSMo: Content-Style Modulation for Image Retrieval with Text Feedback, Seungmin Lee*, Dongwan Kim*, Bohyung Han. *(denotes equal contribution) Setup Python: python3.7 Install required packages Install torch and torchvision via following command (CUDA10) pip install torch==1.2.0 torchvision==0.4.0 -f https://download.pytorch.org/whl/torch_stable.html Install other packages pip install -r requirements.txt Dataset Download the FashionIQ dataset by following the instructions on this link. We have set the default path for FashionIQ datasets in data/fashionIQ.py as _DEFAULT_FASHION_IQ_DATASET_ROOT = ‘/data/image_retrieval/fashionIQ’. You can change this […]

img_sussifier A python script to convert images to animated sus among us crewmate twerk jifs as seen on r/196 Examples How to use install python pip install pillow numpy change input.png to your desired image optionally change output_width in sus.py (output height is calculated automagically) run sus.py upload sussified.gif to r/196 for free karma and also to kill the sus among meme fastermy discord is Lines#9260 send complaints / memes whatever (pls) GitHub https://github.com/LinesGuy/img_sussifier    

Polygonization-by-Frame-Field-Learning This repository contains the code for our fast polygonal building extraction from overhead images pipeline. We add a frame field output to an image segmentation neural network to improve segmentation quality and provide structural information for the subsequent polygonization step. Figure 1: Close-up of our additional frame field output on a test image. Figure 2: Given an overhead image, the model outputs an edge mask, an interior mask,and a frame field for buildings. The total loss includes terms that […]

BMS-Molecular-Translation Pipeline for chemical image-to-text competition. This is a pipeline for Bristol-Myers Squibb – Molecular Translation by Vadim Timakin and Maksim Zhdanov. We got bronze medals in this competition. Significant part of code was originated from Y.Nakama’s notebook This competition was about image-to-text translation of images with molecular skeletal strucutures to InChI chemical formula identifiers. InChI=1S/C16H13Cl2NO3/c1-10-2-4-11(5-3-10)16(21)22-9-15(20)19-14-8-12(17)6-7-13(14)18/h2-8H,9H2,1H3,(H,19,20) Solution General Encoder-Decoder concept Most participants used CNN encoder to acquire features with decoder (LSTM/GRU/Transformer) to get text sequences. That’s a casual approach to […]