Reader () # this needs to run only once to load the model into memory result = reader. Note 2: We also provide a Dockerfile here. If you intend to run on CPU mode only, select CUDA = None. On the pytorch website, be sure to select the right CUDA version you have. Note 1: For Windows, please install torch and torchvision first by following the official instructions here. Add trainer for CRAFT detection model (thanks see PR)įor the latest stable release: pip install easyocrįor the latest development release: pip install git+.It can be used by initializing like this reader = easyocr.Reader(, detect_network = 'dbnet18'). Restructure code to support alternative text detectors. This model is a new default for Cyrillic script. DBnet will only be compiled when users initialize DBnet detector.Add Apple Silicon support (thanks and see PR).Integrated into Huggingface Spaces □ using Gradio. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.Ready-to-use OCR with 80+ supported languages and all popular writing scripts including: Latin, Chinese, Arabic, Devanagari, Cyrillic, etc. This is an application that can also be fetched from. Adobe Photoshop Lightroom and JPhotoTagger both even on different operating systems: JPhotoTagger runs on every system where Java is installed. JPhotoTagger automatically reads tags from new and changed sidecar files and updates it's database. JPhotoTagger is open to work together with other applications such as Adobe Photoshop Lightroom. It speeds up adding or editing tags through automatic keyboard input completion and other features.Īll tags will be written into XMP sidecar files and JPhotoTagger's database. You can manage and find fast your photos through keywords, descriptions and other so called metadata ("tags"). JPhotoTagger is a platform independent Photo Manager.
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