An LPR data analysis package (dev version)!
Project description
LAPIN
What it is
A framework for the analysis of on street parking occupancy via Licence Plate Recognition (LPR) data.
Getting started
Requirements
Install Lapin python's requirments with conda :
conda env create --name <YOUR_ENV_NAME> -f environment.yml
Optional
You may need to have a docker installation available on your machine. See Valhalla mapmatching.
Configuration
Project configuration
Create a config file for your project . You can create a blank one by running :
python -m lapin -c
Mapmatching configuration
You have the choice between two mapmatching engine : OSRM and Valhalla. The main difference being that while using Valhalla you can do the matching directly on the Montreal Geobase. Doing so improve the accuracy of the positionning of the plate on the geobase. Thus improving the quality of the results.
Valhalla
To use valhalla, you'll need to compute the OSM network from the geobase file. Then create the valhalla graph with valhalla engine and the OSM network. The step are the following :
- Create the OSM graph
python -m lapin --generate-graph
- Generate Valhalla's graph
sudo docker run --rm --name valhalla_gis-ops -p 8002:8002 -v $PWD/data/network/valhalla:/custom_files -e tile ghcr.io/gis-ops/docker-valhalla/valhalla:latest'
- Specify the use of valhalla in
lapin/__main__.pyline 113-115.
matcher_host='<PATH_TO_LAPIN>/lapin/data/network/valhalla/valhalla_tiles.tar',
matcher_client='valhalla',
matcher_kwargs={'service_limits':{"trace": {"max_shape": 26000}}}, # your desired config
OSRM
To use OSRM simply identify a valid OSRM instance.
- Specify the use of OSRM in
lapin/__main__.pyline 113-115.
matcher_host=<ADRESS_TO_OSRM_INSTANCE>,
matcher_client='osrm',
matcher_kwargs={},
Note : the instance must be launched with a sufficiently large max-matching-size parameter (e.g. 100000)
Lauching an analysis
Then excecute the package with the following command :
python -m lapin --conf-file <PATH_TO_YOUR_CONF_FILE>
Installing the module
Clone the repo and install the lapin package.
cd <repo_dir>
pip install .
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file onstreet_parking_study_dev-1.2.9.tar.gz.
File metadata
- Download URL: onstreet_parking_study_dev-1.2.9.tar.gz
- Upload date:
- Size: 218.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
64ac1236955293747419ce554713ac422d10b1ffaa485d5651cc298616f1df69
|
|
| MD5 |
5e6bfc135ef4023d260940847cdcc1e2
|
|
| BLAKE2b-256 |
8e673c5d905b4c001c31d18943b1b1992e6da3422e0c561af6500c20e8ef85b2
|
File details
Details for the file onstreet_parking_study_dev-1.2.9-py3-none-any.whl.
File metadata
- Download URL: onstreet_parking_study_dev-1.2.9-py3-none-any.whl
- Upload date:
- Size: 234.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e896d5848b7e5d4da6d7d47ad2121609ccbaaa86af10fe7fb96685602587a3d8
|
|
| MD5 |
54243e8c34b67947951e6c6c76a132b5
|
|
| BLAKE2b-256 |
260042730fe257071b9b5181fde1cc9f9b15569553b0ddef03c694b157eace06
|