How to train your own object detection models using the TensorFlow Object Detection API (2020 Update)
This started as a summary of this nice tutorial, but has since then become its own thing.
| /* | |
| First create a folder inside root directory called *assets* then inside it create another two folders called images and fonts. | |
| Then add your fonts and images(background with logo) | |
| */ | |
| import 'package:flutter/material.dart'; | |
| import 'package:splashscreen_demo/splashscreen.dart'; |
This started as a summary of this nice tutorial, but has since then become its own thing.
| android.permission.ACCESS_ALL_DOWNLOADS | |
| android.permission.ACCESS_BLUETOOTH_SHARE | |
| android.permission.ACCESS_CACHE_FILESYSTEM | |
| android.permission.ACCESS_CHECKIN_PROPERTIES | |
| android.permission.ACCESS_CONTENT_PROVIDERS_EXTERNALLY | |
| android.permission.ACCESS_DOWNLOAD_MANAGER | |
| android.permission.ACCESS_DOWNLOAD_MANAGER_ADVANCED | |
| android.permission.ACCESS_DRM_CERTIFICATES | |
| android.permission.ACCESS_EPHEMERAL_APPS | |
| android.permission.ACCESS_FM_RADIO |
| var serialport = require('node-serialport') | |
| var sp = new serialport.SerialPort("/dev/ttyO3", { | |
| parser: serialport.parsers.raw, | |
| baud: 9600 | |
| }) | |
| sp.on('data', function(chunk) { | |
| console.log(chunk.toString('hex'), chunk.toString(), chunk) | |
| }) |
| // | |
| // !!WARNING: Not recommended for production code!! | |
| // | |
| public class ClassLoaderActivity extends Activity | |
| { | |
| public void onCreate(Bundle savedInstanceState) | |
| { | |
| // file.jar has a dex'd "classes.dex" entry that you can generate with "dx" from any number of JARs or class files | |
| ClassLoader dexLoader = new DexClassLoader("/path/to/file.jar", getCacheDir().getAbsolutePath(), null, getClassLoader()); | |
| setAPKClassLoader(dexLoader); |