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numericvision\n\nA Python 3 package for detecting numeric \n[seven-segment displays](https://en.wikipedia.org/wiki/Seven-segment_display) in images and running \n[perspective correction](https://en.wikipedia.org/wiki/Perspective_control) on them using \n[OpenCV 4](https://opencv.org).\n\n`detect_box_sequences()` first applies a series of filters to the input image to reduce noise, bring\nout primary contours and bridge gaps between digit segments (see `images.apply_filters()`). Next,\nall resulting contours are analyzed by comparing their geometric properties to a set of criteria\nwhich define what it means for a contour to resemble a seven-segment digit. Lots of assumptions are\nbeing made here (see `config.cfg`). A contour resembling a seven-segment digit is used to\ninstantiate a `Box` object. Several boxes lined up in a row make up a box `Sequence`. Sequences are\ncontained in a `Bag`.\n\nIn other words, raw contours serve as input for an object detection pipeline which produces results\nin the form of a crawlable object tree.\n\n![Demo](tests/demo.jpg)\n\n## Installation\n\n```\n$ brew install opencv\n```\n```\n$ pip install numericvision\n```\n\n## Using the package\n\n```python\nfrom numericvision import detect_box_sequences\n\nbox_sequences = detect_box_sequences(\"image.jpg\")\n```\n\n## Running from the command line\n\n```\n$ python -m numericvision image.jpg\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Figorm%2Fnumericvision","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Figorm%2Fnumericvision","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Figorm%2Fnumericvision/lists"}