gallerize Create a static HTML/CSS image gallery from a bunch of images. Features Integrates ImageMagick to resize images and create thumbnails. Generates clean, slim, semantically appropriate HTML5 and uses CSS 3 for styling. As a result, the output can easily be themed. Provides HTML access keys for keyboard navigation. Optimizes images to reduce size and remove metadata. Requirements Installation It is recommended to create a virtual environment and run gallerize inside it. To install ImageMagick, jpegoptim, and virtualenv on Debian/Ubuntu: […]

Image Processing OpenCV This repository is focused on having various feature implementation of OpenCV in Python. The aim is to have a minimal implementation of all OpenCV features together, under one roof. This repository is focused on having various feature implementations of OpenCV in Python. About OpenCV: OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use […]

GeoGIF Make GIFs from time-stacked xarray.DataArrays (time, [optional band], y, x), dead-simple. from geogif import gif, dgif gif(data_array) dgif(dask_data_array).compute() The “geo” part is a lie, actually. The arrays don’t have to be geospatial in nature. But I called it GeoGIF because: Wanting to animate a time-stack of imagery (like you’d get from stackstac) is a common task in the earth-observation/geospatial world. I think GeoGIF is a hilarious idea1. 1: To ruin the joke, it sounds like GeoTIFF, a ubiquitous geospatial […]

Pillow Pillow is the friendly PIL fork by Alex Clark and Contributors. PIL is the Python Imaging Library by Fredrik Lundh and Contributors. As of 2019, Pillow development is supported by Tidelift. The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It […]

Color & Depth Renderer for ShapeNet This library includes the tools for rendering multi-view color and depth images of ShapeNet models. Physically based rendering (PBR) is featured based on blender2.79. Outputs Color image (20 views) Depth image (20 views) Point cloud and normals (Back-projected from color & depth images) Watertight meshes (fused from depth maps) Install We recommend to install this repository with conda. conda env create -f environment.yml conda activate renderer Install Pyfusion by cd ./external/pyfusion mkdir build cd […]

starfish starfish: scalable pipelines for image-based transcriptomics starfish is a Python library for processing images of image-based spatial transcriptomics. It lets you build scalable pipelines that localize and quantify RNA transcripts in image data generated by any FISH method, from simple RNA single-molecule FISH to combinatorial barcoded assays. If you want to give it a try, the quick start tutorial will guide you from installation to running a pipeline in under 10 minutes. For more comprehensive instructions on how to […]

TagLab TagLab was created to support the activity of annotation and extraction of statistical data from ortho-maps of benthic communities. The tool includes different types of CNN-based segmentation networks specially trained for agnostic (relative only to contours) or semantic (also related to species) recognition of corals. Interaction TagLab allows to : zoom and navigate a large map using (zoom/mouse wheel, pan/’Move’ tool selected + left button). With every other tool selected the pan is activated with ctrl + left button […]

DALLE-reproduction This repository is for sharing pre-trained OpenAI DALLE model and generating images from given texts. All models are trained by lucidrains/DALLE-pytorch + VQGAN (Taming transformer) with different training code and BPE model. The notebook includes Text to image generation Pre-trained CLIP reranking 3. Generate rest of image based on the given cropped image Usage Install requirements $ pip install -r requirements Install DeepSpeed Follow the instruction here and install DeepSpeed Models Download models below and save them in pretrained […]

Curator Self-supervised learning is a subfield of machine learning focused on developing representations of images without any labels, which is useful for reverse image searching, categorization and filtering of images, especially so when it would be infeasible to have a human manually inspect each individual image. It also has downstream benefits for classification tasks. For instance, training SSL on 100% of your data and finetuning the encoder on the 5% of data that has been labeled significantly outperforms training a […]