{
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        "author": "[ods.ai] Arseny Kravchenko et al",
        "author_email": "",
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            "Programming Language :: Python :: 3.6",
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        "description": "[![Build status](https://badge.buildkite.com/3be2c7533d11e157a0b1fef8af1231356349694c459f072ccc.svg)](https://buildkite.com/ceevee/ceevee-tests)\n\n# ceevee\n\n`ceevee` (read like CV, i.e. computer vision) is a Python library for various computer vision problems with a focus on easy usage.\n\n`ceevee` aims to be a bridge between deep learning practitioners training accurate models and product-oriented software engineers who just want to process their images instead of diving into the deep learning ecosystem.\n\nPython 3.6+ is supported.\n\n## Install\n\nFrom PyPI - not available yet\n\nFrom source\n```\npython setup.py bdist_wheel\npip install -U ceevee-0.0.1-py3-none-any.whl\n```\n\n## Tasks\n\n## Usage\n\nAll tasks shares the same API\n\n### CLI API\n\n`python -m ceevee.cli task /path/to/img1.jpg /path/to/img2.jpg ... /path/to/imgN.jpg > result.json`\n\n### HTTP API\n\nHTTP API is based on [Falcon](https://github.com/falconry/falcon),\nso it can be used with any WSGI server, such as uWSGI or Gunicorn.\n\n- install your favourite WSGI server (e.g. `pip install gunicorn`)\n- set env variable `CEEVEE_TASKS` for your tasks,\n multiple comma separated tasks are supported, e.g. `CEEVEE_TASKS=task1,task2` \n- run a server `CEEVEE_TASKS=dummy gunicorn ceevee.cv_http`;\n- send a POST request with `image` parameter. \n\n```\n$ http -f POST localhost:8000/dummy image@/tmp/img.jpg\nHTTP/1.1 200 OK\nConnection: close\nDate: Sat, 14 Sep 2019 13:47:39 GMT\nServer: gunicorn/19.9.0\ncontent-length: 37\ncontent-type: application/json\n\n{\n    \"result\": [\n        500,\n        500,\n        3\n    ],\n    \"success\": true\n}\n```\n\n### Python API\n\n```python\nfrom ceevee.utils import read_img\nfrom ceevee.dummy import DummyPredictor\nbaseline = DummyPredictor()\nimg = read_img('/path/to/img.jpg')\nresult = baseline(img)\n```\n\n## Contributions\n\nYes, you can add a new model!\n\n### Checklist:\n- create a GitHub issue with your suggested model;\n- create a new Baseline class (see `ceevee.dummy.DummyBaseline`) and implement three methods (`preprocess`, `process`, \n`postprocess`);\n- add your model to `MODELS` at `ceevee/__init__.py`\n- add tests to `tests/`;\n- once CI is green, create a pull request!\n\n# ToDo:\n\n- infrastructure:\n    - packaging, pip\n- APIs:\n    - http: tests, error handling \n- models: \n    - face detection\n    - face emotion\n    - face keypoints \n    - car detection\n    - crowd density estimation",
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        "keywords": "Machine Learning,Deep Learning,Computer Vision,PyTorch",
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