- support gis (datum wgs84)
- support glob 3d earth
- map tms wms(local vector maps raster)
- train hight (tms wms)
- gis basic tools (ppi los roller)
Installation of Tensorflow2 with GPU support is easy and the only complication can be arisen from the CUDA compability which in turns depends on the Nvidia driver version. Before going farther, please check if your Nvidia Video Card is compatible with the required versions that are defined in this gist, use this link.
Tensorflow offers in its website a table of the compatibility between libraries for the target OS. You can visit that website in the following COMPATIBILITY TABLE that points to the Tensorflow installation from source for linux. For the time writing this gist, Tensorflow2 v2.5.0 requires CUDA v11.2 and CUDNN v8.2. It is really important to match the exact version, otherwise tensorflow will have problems loading the shared libraries as not finding the correct version.
CUDA version also requires for a minimum Nvidia driver version
# Tested on Python 3.6.1 | |
# install: pip install --upgrade arabic-reshaper | |
import arabic_reshaper | |
# install: pip install python-bidi | |
from bidi.algorithm import get_display | |
# install: pip install Pillow | |
from PIL import ImageFont |
node_modules | |
dist/ | |
yarn.lock | |
wwwroot |
:: Build client | |
RunUAT BuildCookRun -project="full_path.uproject"^ | |
-noP4 -platform=Win64^ | |
-clientconfig=Development -serverconfig=Development^ | |
-cook -allmaps -build -stage^ | |
-pak -archive -archivedirectory="Output Directory" | |
:: Cook client | |
RunUAT BuildCookRun -project="full_project_path_and_project_name".uproject^ | |
-noP4 -platform=Win64^ |
Moved to git repository: https://github.com/denji/nginx-tuning
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon
with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
// usage: | |
// | |
// TesseractOCR ocr = TesseractOCR(@"C:\bin\tesseract.exe"); | |
// string result = ocr.OCRFromBitmap(bmp); | |
// textBox1.Text = result; | |
// | |
using System; | |
using System.IO; | |
using System.Diagnostics; | |
using System.Drawing; |