CPU : Intel® Core™ i9-7900X CPU @ 3.30GHz x 20
GPU : TITAN Xp/PCle/SSE2 (CUDA 9.0)
RAM : 32GB
OS : CentOS 7 (64bit)
DB : PostgreSQL 11 ( + plpython3u, PostGIS 2.4, DeepGeoEngine 3.1903141530)
LIB : Python 3.6 ( + Keras, Tensorflow, CPython, skimage, matplotlib, piexif, PIL, exifread etc.)
Result
Function Information
< DeepGeo Setting SQL >
# Setup for Engine# - Engine raise to memory.# - model : The selected model is set as default model.# return : nullSELECT M_deepSetup(model text);
SELECT M_deepSetup(); # Default Model : mscocoSELECT M_deepModelList(); # Get Model ListSELECT M_deepClassList(model_name text);
SELECT M_deepClassList(); #
< Detect SQL >
# Detect # - image detect.# - file_url : The file path it want analyze.# - model_name : The selected model is set as detect model.# return : JSON (OR None) SELECT M_deepDetect(file_url text, model_name text);
SELECT M_deepDetect(file_url text); # Default Model : mscoco (Depends on the M_deepSetup option.)# Count Object# - Number of Object# - file_url : file path it want analyze.# - category : Object you are looking for.# - model_name : The selected model is set as detect model.# return : INTEGERSELECT M_deepCount(file_url text, category text, model_name text);
SELECT M_deepCount(file_url text, category text); # Default Model : mscoco (Depends on the M_deepSetup option.)SELECT M_deepCount(file_url text); # Number of all object.# Find pictures of more than three people.SELECT*FROM tb_image WHERE M_deepCount(url, 'person', 'mscoco') >=3;
# Find pictures with between 3 cars and 5 cars.SELECT*FROM tb_image WHERE M_deepCount(url, 'car') BETWEEN 3AND5;
# Find pictures that have people and cars. SELECT*FROM tb_image WHERE M_deepCount(url, 'car') >0AND M_deepCount(url, 'person') >0;
# All count obejct# - All Number of Object# - file_url : file path it want analyze.# - category : Objects you are looking for.# - model_name : The selected model is set as detect model.# return : JSONSELECT M_deepCountAsJSON(file_url text, category text, model_name text);
SELECT M_deepCountAsJSON(file_url text, category text); # Default Model : mscoco (Depends on the M_deepSetup option.)SELECT M_deepCountAsJSON(file_url text); # All category# Find Object# - Find Object# - file_url : file path it want analyze.# - category : Objects you are looking for.# - model_name : The selected model is set as detect model.# return : JSONSELECT M_deepFind(file_url text, category text, model_name text);
SELECT M_deepFind(file_url text, category text); # Default Model : mscoco (Depends on the M_deepSetup option.)SELECT M_deepFind(file_url text); # All category
< Image Data SQL >
# EXIFSELECT M_deepImgExif(file_url text, key text);
SELECT M_deepImgHeight(file_url text);
SELECT M_deepImgWidth(file_url text);
SELECT M_deepImgAltitude(file_url text);
SELECT M_deepImgDirection(file_url text);
SELECT M_deepImgDistance(file_url text);
SELECT M_deepImgLoc(file_url text); # It will change the name to M_deepImgLocation SELECT M_deepImgLocAsJson(file_url text); # It will change the name to M_deepImgLocationAsJsonSELECT M_deepImgVerticalAngle(file_url text);
SELECT M_deepImgViewAngle(file_url text);
SELECT M_deepImgfov(file_url text);
SELECT M_deepImgfov(file_url text, view_angle double precision);
SELECT M_deepImgfov(file_url text, view_angle double precision, distance double precision);
SELECT M_deepImgDate(file_url text);
SELECT M_deepImgTimeStamp(file_url text);
# GET BINARY IMAGESELECT M_deepImgfile(file_url text);
SELECT M_deepImgfile(file_url text, model_name text);
< PostGIS >
SELECT M_deepGeoFovIntersection(url text, geo geometry);
SELECT M_deepGeoFovIntersection(url1 text, url2 text);
SELECT M_deepGeoAnnotation(photo stphoto); # It's not support now.
> su postgres
> cd /var/lib/pgsql/11/data/
> wget https://github.com/awarematics/postgeomedia/tree/dg
> tar -zxvf API3.tar.gz
5. SQL Insert
Go To https://github.com/awarematics/postgeomedia/blob/dg/sql/01.install/1.install_deepgeo_plpython_function.sql
Copy ALL
PostgreSQL New Query And Paste and Run