{ "info": { "author": "Michael Sugimura", "author_email": "deepak.kumar.iet@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 3" ], "description": "\n\ud83d\udc26 multi_label_pigeon\n========================\n\nThis repo is a simple multiclass image extenstion of the pigeon library by\n@agermanidis located [here](https://github.com/agermanidis/pigeon). Credit goes to them for building\nthe annotate function for images, text, and regression for multi-class type problems. All I am doing is extending it to multi-label and multi-task type problems.\n\n## Installation\n\nCan install with standard pip.\n\n```\npip install multi-label-pigeon\n```\n\n\n## Examples\n\n```\nfrom multi_label_pigeon import multi_label_annotate\nfrom IPython.display import display, Image\n\nannotations = multi_label_annotate(\n ['assets/altera.jpg', 'assets/chibi_gil.jpg','assets/chibi_saber.jpg'],\n options={'cute':['yes','no'], 'saber':['yes','no'],'colors':['blue','gold','white','red']},\n display_fn=lambda filename: display(Image(filename))\n )\n```\nPreview:\n\n![alt text](/assets/sample_usage5.gif)\n\n## Additional Notes\n____\nI added some additional buttons as well to the multi-label script. Since we want to be able to select more than one category I added a few extra buttons.\n\n- `done` button to press after all relevant fields have been clicked. \n\n- `back` button in case you want to go back to a previous image. **WARNING** this will erase that item from the dictionary so you will have to click through all the classes you want to mark for that previous image again. \n![back_example](/assets/back.gif)\n\n- `clear current` **WARNING** will delete the current image from the dictionary on the back end so you can re enter the classes in case you messed one up.\n![clear_current](/assets/clear_current2.gif)\n\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://https://github.com/sugi-chan/multi_label_pigeon", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "multi-label-pigeon", "package_url": "https://pypi.org/project/multi-label-pigeon/", "platform": "", "project_url": "https://pypi.org/project/multi-label-pigeon/", "project_urls": { "Homepage": "https://https://github.com/sugi-chan/multi_label_pigeon" }, "release_url": "https://pypi.org/project/multi-label-pigeon/0.2.0/", "requires_dist": [ "ipywidgets" ], "requires_python": "", "summary": "A way to label multi label image datasets in jupyter", "version": "0.2.0" }, "last_serial": 5793896, "releases": { "0.1.1": [ { "comment_text": "", "digests": { "md5": "a8755875ac4f3adb78a3f4f2518d67ed", "sha256": "508fcfc673bed5e2d6b9ea6f64b756d7f45320b75d15fa1594f2b28a2cf03167" }, "downloads": -1, "filename": "multi_label_pigeon-0.1.1-py3-none-any.whl", "has_sig": false, "md5_digest": "a8755875ac4f3adb78a3f4f2518d67ed", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 4559, "upload_time": "2019-09-06T20:00:41", "url": "https://files.pythonhosted.org/packages/bf/cb/15088286f7e17d489f0c63595436fcb8227f4d37cc2ffb4a1d4fa2c0647b/multi_label_pigeon-0.1.1-py3-none-any.whl" } ], "0.1.2": [ { "comment_text": "", "digests": { "md5": "0e0f7a538ad0a4d23c096df4399078cc", "sha256": "753c6d35be44743325a12f0b77b214ba2b6760b2607562fdb860a50781f3d4d5" }, "downloads": -1, "filename": "multi_label_pigeon-0.1.2-py3-none-any.whl", "has_sig": false, "md5_digest": "0e0f7a538ad0a4d23c096df4399078cc", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 4508, "upload_time": "2019-09-06T20:44:03", "url": "https://files.pythonhosted.org/packages/8d/41/da3d6ef0ebfa56e72eb6f8ec775e898ee9d7bc99f120495ac1c0d36221e5/multi_label_pigeon-0.1.2-py3-none-any.whl" } ], "0.2.0": [ { "comment_text": "", "digests": { "md5": "888c89dcf8be002f805d633e11ef8415", "sha256": "2e11bf100328355bf295b814ba478f6430835fd62fce3e83c52d53c4a2419464" }, "downloads": -1, "filename": "multi_label_pigeon-0.2.0-py3-none-any.whl", "has_sig": false, "md5_digest": "888c89dcf8be002f805d633e11ef8415", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 4515, "upload_time": "2019-09-06T20:58:53", "url": "https://files.pythonhosted.org/packages/ca/10/d3442651c6a2bd8563a02881752ec0ad0a91a8e29f7a6dbfd18093a983d2/multi_label_pigeon-0.2.0-py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "888c89dcf8be002f805d633e11ef8415", "sha256": "2e11bf100328355bf295b814ba478f6430835fd62fce3e83c52d53c4a2419464" }, "downloads": -1, "filename": "multi_label_pigeon-0.2.0-py3-none-any.whl", "has_sig": false, "md5_digest": "888c89dcf8be002f805d633e11ef8415", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 4515, "upload_time": "2019-09-06T20:58:53", "url": "https://files.pythonhosted.org/packages/ca/10/d3442651c6a2bd8563a02881752ec0ad0a91a8e29f7a6dbfd18093a983d2/multi_label_pigeon-0.2.0-py3-none-any.whl" } ] }