Package: secv-guis
SECV GUIsRepository hosting diverse Python3 Qt GUIs made at the Systems Engineering and Computer Vision Department @ Goethe University Frankfurt.DEMOS:Bimask App:This application allows the user to load, edit and save different annotations and pre-annotations for high-resolution images. Note that the GUI doesnotintegrate the pre-annotation vision modules, it simply loads their results from the filesystem. For more details see theinstructionsInstall and run:The recommended way is to install from PyPI via command line interface. Using a fresh environment, it would look like this:cd /tmp
virtualenv -p python3 venv
source venv/bin/activate
pip install secv-guis
python -m secv_guisYou can also clone this package from GitHub, or pull the latest release:https://github.com/andres-fr/secv-guis/releasesThe badges above link to the documentation and PyPI webpages. Please let me know if you encounter any issue!Developers:The project is split in 2 main parts: the modules at the top level contain reusable parts (library-space). Each directory contains then an application (app-space).
To create a new app, make a new folder with your desired app-specific contents, and include it into__main__. If you develop reusable contents, consider adding them to the top-level modules to be used in further apps. Conversely, avoid API-breaking changes into the reusable components, unless you make sure that all the apps are conveniently updated.The.travis.ymlfile contains examples on how to run code style check, unit tests with coverage, build and autodoc. You can see more detailed information here:https://github.com/andres-fr/python3-template/blob/master/README.mdAlso, the documentation for this own repository should help extending the software:https://secv-guis.readthedocs.io/en/latest/?badge=latestRationale:The necessity of the bi-mask annotation GUI was concluded after conversations with the Civil Engineers, and driven by our struggling attempts to annotate cracks with pixel-precision consistently from different setups. When looking for existing tools, we needed a python-based extendable tool that would allow for "free painting"  as well as combining preannotations with annotations. It should be reasonably responsive when working with high-resolution images.The following is the result of an exhaustive search of available OSS labeling tools whose functionality would intersect with our requirements. No existing tool matched them close enough, most of them lacking pixel-precise segmentation, a.k. "free painting", or integration of preannotated masks. A list can be foundhere:labelImg- LabelImg is a graphical image annotation tool and label object bounding boxes in imagesCVAT- Powerful and efficient Computer Vision Annotion Toollabelme- Image Polygonal Annotation with PythonVoTT- An open source annotation and labeling tool for image and video assetsimglab- A web based tool to label images for objects that can be used to train dlib or other object detectorsYolo_mark- GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2PixelAnnotationTool- Software that allows you to manually and quickly annotate images in directoriesOpenLabeling- Label images and video for Computer Vision applicationsimagetagger- An open source online platform for collaborative image labelingAlturos.ImageAnnotation- A collaborative tool for labeling image datadeeplabel- A cross-platform image annotation tool for machine learningMedTagger- A collaborative framework for annotating medical datasets using crowdsourcing.Labelbox- Labelbox is the fastest way to annotate data to build and ship computer vision applicationsturktool- A modern React app for scalable bounding box annotation of imagesPixie- Pixie is a GUI annotation tool which provides the bounding box, polygon, free drawing and semantic segmentation object labellingOpenLabeler- OpenLabeler is an open source desktop application for annotating objects for AI appplicationsAnno-Mage- A Semi Automatic Image Annotation Tool which helps you in annotating images by suggesting you annotations for 80 object classes using a pre-trained modelCATMAID- Collaborative Annotation Toolkit for Massive Amounts of Image Datamake-sense- makesense.ai is a free to use online tool for labelling photosLOST- Design your own smart Image Annotation process in a web-based environment