Ceevee
Python library for various computer vision problems with a focus on easy usage.
Install / Use
/learn @arsenyinfo/CeeveeREADME
ceevee
ceevee (read like CV, i.e. computer vision) is a Python library for various computer vision problems with a focus on easy usage.
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.
Python 3.6+ is supported.
Install
From PyPI
pip install -U ceevee
From source
python setup.py bdist_wheel
pip install -U ceevee-0.0.1-py3-none-any.whl
Tasks
Usage
All tasks shares the same API
CLI API
python -m ceevee.cli task /path/to/img1.jpg /path/to/img2.jpg ... /path/to/imgN.jpg > result.json
HTTP API
HTTP API is based on Falcon, so it can be used with any WSGI server, such as uWSGI or Gunicorn.
- install your favourite WSGI server (e.g.
pip install gunicorn) - set env variable
CEEVEE_TASKSfor your tasks, multiple comma separated tasks are supported, e.g.CEEVEE_TASKS=task1,task2 - run a server
CEEVEE_TASKS=dummy gunicorn ceevee.cv_http; - send a POST request with
imageparameter.
$ http -f POST localhost:8000/dummy image@/tmp/img.jpg
HTTP/1.1 200 OK
Connection: close
Date: Sat, 14 Sep 2019 13:47:39 GMT
Server: gunicorn/19.9.0
content-length: 37
content-type: application/json
{
"result": [
500,
500,
3
],
"success": true
}
Python API
from ceevee.utils import read_img
from ceevee.dummy import DummyPredictor
baseline = DummyPredictor()
img = read_img('/path/to/img.jpg')
result = baseline(img)
Contributions
Yes, you can add a new model!
Checklist:
- create a GitHub issue with your suggested model;
- create a new Baseline class (see
ceevee.dummy.DummyBaseline) and implement three methods (preprocess,process,postprocess); - add your model to
MODELSatceevee/__init__.py - add tests to
tests/; - once CI is green, create a pull request!
ToDo:
- APIs:
- http: finalize tests, error handling
- actual models:
- face detection
- face emotion
- face keypoints
- car detection
- crowd density estimation
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