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        "author": "Henri-Louis Girard",
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        "description": "# xptools\n\n[![PyPI version](https://badge.fury.io/py/xptools.svg)](https://badge.fury.io/py/xptools)\n\nAnalysis tools for experimental sciences to display images, detect particles (cells, bubbles, crystals), moving fronts and analyze their shape, size and distibution.\n\n## Installation\n\nxptools is on PyPI so you can install it straight from pip with the command\n\n```\npip install xptools\n```\n\nAlternatively, you can clone the repository to your local computer and install from source\n\n```\ngit clone https://github.com/hlgirard/xptools\ncd xptools\npip install .\n```\n\n## Scripts\n\n- analyze_front - This scipt takes a directory containing video files. For each file, it asks the user to select a region of interest\nand processes the selected area with a minimum threshold to find the largest area. It then plots the height of this area as\na function of time.\n\n```\nanalyze_front --plotly --scale 60 --framerate 30 moviedirectory/\n```\n\n![screenshot](docs/screenshots/analyze_front_ex-01.jpg)\n\n- analyze_bubbles - This script takes a movie (or directory of movies) showing bubbles on a surface (bright on dark). It uses a watershed segmentation algorithm to identify the bubbles and characterize their size. It then plots the bubble density and mean size as a function of time.\n\n```\nanalyze_bubbles --plotly --scale 60 bubble_movie.avi\n```\n\n![screenshot](docs/screenshots/analyze_bubbles_ex-01.jpg)\n\n- analyze_crystals - This script takes a directory containing pictures of droplets containing crystals (under cross polarization). It uses a thresholding algorithm to segment the crystals, count them and measure their size.\n\n```\nanalyze_crystals --plotly --key funct_key.txt imagedirectory/\n```\n\n![screenshot](docs/screenshots/analyze_crystals_ex-01.jpg)\n\n- display_image_matrix - Arranges all the images in a directory as a matrix and saves the resulting image\n\n```\ndisplay_image_matrix --lines 10 --compress imagedirectory/\n```\n\n## Utilities\n\nSeveral utilities are included in the submodule utils including:\n\n- select_roi:select_rectangle - Prompts the user to make a rectangular selection on the passed image and returns the coordinates of the selection.\n\n- videotools:open_video - Opens a video file as a list of np.arrays each containing one frame of the video.\n\n- videotools:determine_threshold - Determines the threshold to use for a video based on the minimum threshold algorithm.\n\n- videotools:obtain_cropping_boxes - Prompts the user to select the region of interest for each video file. Returns a dataframe containing the coordinates of the selected area for each file.\n\n- imagetools:open_all_images - Opens all the images in a folder and returns a list of cv2 images.\n\n### Example usage\n\n```python\nimport pandas as pd\nfrom xptools.utils import videotools\n\nvideo_list = ['Film1.avi','Film2.avi']\n\ndict_crop = videotools.obtain_cropping_boxes(video_list)\n\nfor key, val in dict_crop:\n    stack = videotools.open_video(key)\n    (minRow, minCol, maxRow, maxCol) = val\n    stack = [img[minRow:maxRow,minCol:maxCol] for img in stack]\n    process(stack)\n```\n\n## Notebooks\n\n- SegmentationBroadSpectrum.ipynb - Tests different image segmentation techniques to determine which is most appropriate\n- SegmentationFocused.ipynb - Implements a specific analysis and plots the resulting size and number distributions for the particles\n- Watershed_Segmentation.ipynb - Implements Watershed segmentation.\n\n## Credits\n\nCode for display_image_matrix adapted from https://gist.github.com/pgorczak/95230f53d3f140e4939c#file-imgmatrix-py\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.\n\n\n",
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