This repository contain all util
Project description
DPS_Util
This repository contain all util.
Install:
Get at https://pypi.org/project/dpsutil/
pip install dpsutil
Change log:
Ver 1.0.0:
- Compression -> DONE
- KafkaWrapper -> DONE
- RedisWrapper -> DONE
- Vector -> DONE
- Media -> DONE
- Computer Vision -> DONE
- Distance -> DONE
- Hashing -> DONE
Ver 1.0.1:
- Added image_info -> Get (format, width, height) of image without decoding.
- Upgrade imdecode -> Auto decode image but need not provide encode_type.
Ver 1.0.2:
- Change 'numpy.pool' to 'vector.pool'
- Fix bugs
Ver 1.0.3:
- Compression:
- Support list compression: compress_list, decompres_list
- Distance:
- Change distance.function -> vector.distance
Ver 1.1.0:
- Added AttrDict, FixedDict, FixedTypeDict
Ver 1.1.1-1.1.7:
- Fix bugs
- Added UniqueTypeDict
- Fix bugs
- Changed module fixdict -> defaultdict
- Changed FixedDict -> DefaultDict
- Changed FixedTypeDict -> DefaultTypeDict
- Fix bugs of attrdict.AttrDict, attrdict.UniqueTypeDict, attrdict.DefaultDict
- Fix bugs of compress_list, decompress_list
Ver 1.1.8:
- Added Environment
Ver 1.1.9-1.1.18:
- Added Environment.to_lower -> Useful when extracting to kwarg.
- Fix bugs attrdict
- Changed hashfunc default from sha1 -> md5
- Support call of DefaultDict, which update data from buffer.
- Fix bugs Environment
Ver 1.1.19:
- Added pre-define output array of decompress_ndarray
- Support add new key environment.
Ver 1.1.20-1.1.21:
- Edit logger
- Fix bugs vector.pool
- Changed VectorPool base on numpy.mmap -> VectorPoolMMap
- Added VectorPool base on numpy.ndarray
- Restructure VectorPoolBase -> Speed up, fix bugs
- Added VectorPoolBase.insert
Ver 1.1.22:
- Add document of compression, media module.
- Fix bugs image
- Change media.image.scale -> media.image.zoom
Ver 1.1.23-24:
- Fix bugs log
- Fix bugs VectorPoolMMap.MIN_SIZE
Ver 1.1.25-26:
- Fix bugs attrdict
- Added add, remove method attrdict
- Rename variable of pool.VectorPoolBase
Ver 1.1.27:
- Change namespace attrdict.UniqueTypeDict -> attrdict.TypedDict
- Restructure attdict.AttrDict, attdict.DefaultDict, attrdict.TypedDict
- Support annotations alias
- Speed up attrdict
- Support initial attrdict with iterable, generator.
- Support to_buffer method with optimize compression.
- Support recreate dict with from_buffer.
- Lightweight than pickle.dumps
Ver 1.2.0:
- CV:
- Added Face Aligner
- Transforms image methods
- media.image:
- Added scale, crop_center, flip
- Fix bugs
- media.video: support FPS report.
- triangle (new)
Ver 1.3.0:
- Support decorator attrdict
- Support decorator environment
- Implemented Confluent-Kafka with:
- Iterator method
- Close event.
- Auto_commit
- Optimize configs for ThroughOut
- Fix bug KafkaError
Todo:
- Implement Configs librdkafka
- Sort -> implement natsort - https://github.com/SethMMorton/natsort
Features
Compression Lossless:
- Support type: ndnumpy, bytes
- Compress by blosc. It support multi compressor and multi-thread.
KafkaWrapper:
- Wrapping Consumer and Producer with default setting and security.
RedisWrapper
- Wrapping Redis Connector with default setting and security.
Vector Pool:
VectorPoolBase handle numpy.ndarray that save a lot of RAM by re-use existed memory space.
Easier than numpy.ndarray. Likely list.
- Reduce RAM
- High Speed IO
- Auto Scale
- Support backup and recovery data in a second.
Media:
Implemented OpenCV with:
- TurboJPEG (https://github.com/lilohuang/PyTurboJPEG)
- FFmpeg(https://github.com/kkroening/ffmpeg-python)
To: improve read & write (image, video) IO speed.
-
Faster than OpenCV:
- 2-6x with JPEG Encoder
- 1.1x with others.
-
Added some function which used frequently.
-
More info: find in dpsutil.media
Computer Vision (cv):
- Added Face Align with five landmark.
Distance:
- Added cosine_similarity
- Added cosine
- Added euclidean_distance
- Added convert distance functions
*Note: all function execute in numpy.
Attributes dict:
- AttrDict: will help you get value of key via attributes. Implement attrdict.AttrDict
- DefaultDict: help cover your dict with (keys, values) that was defined before. Implement from AttrDict
- TypedDict: help cover your dict when set item. Implement from AttrDict.
- DefaultTypeDict: dict only access one type for all element.
- Support initial attrdict with iterable, generator.
- Support to_buffer method with optimize compression.
- Support recreate dict with from_buffer.
- Lightweight than pickle.dumps
Environement:
- Environment: Auto pair environment parameters fit with default, which provided before.
Other:
- Hashing
- Sort
Issue:
Cmake error during install blosc
Firstly, you need install scikit
$ pip install scikit-build
After that, follow instuction to install Cmake:
https://cliutils.gitlab.io/modern-cmake/chapters/intro/installing.html
Python
$ pip install cmake>=3.12
Not found 'FFmpeg':
Find FFmppeg lib at:
Linux:
sudo apt-get install ffmpeg
Not found 'libjpeg-turbo':
Find FFmppeg lib at:
Linux:
$ sudo apt install libturbojpeg
Not found Redis or Kafka server:
- Make sure your Redis or Kafka server started.
- Make sure correct username & password.
Not found 'Could NOT find OpenSSL':
SSL development libraries have to be installed
Ubuntu:
$ apt-get install libssl-dev libffi-dev
Develop by: TinDang
OS: Ubuntu Bionic 18.04
Python: 3.6.9 stable
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