yptheangel

(base) D:\Efficient-PyTorch\tools>python folder2lmdb.py -f "C:\Users\ChooWilson\.fastai\data\kaggle-cat-dog" -s train
Loading dataset from C:\Users\ChooWilson\.fastai\data\kaggle-cat-dog\train
Generate LMDB to C:\Users\ChooWilson\.fastai\data\kaggle-cat-dog\train.lmdb
2000 2000
Traceback (most recent call last):
  File "folder2lmdb.py", line 181, in <module>
    folder2lmdb(args.folder, num_workers=args.procs, name=args.split)
  File "folder2lmdb.py", line 150, in folder2lmdb
    for idx, data in enumerate(data_loader):
  File "C:\Users\ChooWilson\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 279, in __iter__

yptheangel

#Original source from https://github.com/opencv/opencv/blob/master/samples/python/tutorial_code/ShapeDescriptors/hull/hull_demo.py

from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng

rng.seed(12345)

yptheangel

class myCallback(tf.keras.callbacks.Callback):
  def on_epoch_end(self, epoch, logs={}):
    if(logs.get('acc')>0.6):
      print("\nReached 60% accuracy so cancelling training!")
      self.model.stop_training = True

yptheangel

import org.bytedeco.ffmpeg.global.avcodec;
import org.bytedeco.ffmpeg.global.avutil;
import org.bytedeco.javacv.*;
import org.bytedeco.opencv.opencv_core.*;
import static org.bytedeco.opencv.global.opencv_imgproc.*;
import static org.bytedeco.opencv.helper.opencv_core.RGB;
import org.bytedeco.opencv.opencv_videoio.VideoWriter;
import org.datavec.image.loader.NativeImageLoader;
import org.datavec.image.transform.ColorConversionTransform;
import org.deeplearning4j.nn.graph.ComputationGraph;

yptheangel

int baseline[]={0};
Size textSize=getTextSize("Hello World", FONT_HERSHEY_DUPLEX, 1,1,baseline);
int textwidth=textSize.get(0);
int textheight=textSize.get(1);
rectangle(yourMat, new Point(x1 + 2, y2 - 2), new Point(x1 + 2+textwidth, y2 - 2-textheight),RGB(255,255,0), FILLED,0,0);
putText(yourMat, "Hello World", new Point(x1 + 2, y2 - 2), FONT_HERSHEY_DUPLEX, 1, RGB(0,0,0));

yptheangel

int baseline[]={0};
Size textSize=getTextSize("Hello World", FONT_HERSHEY_DUPLEX, 1,1,baseline);
int textwidth=textSize.get(0);
int textheight=textSize.get(1);
rectangle(yourMat, new Point(x1 + 2, y2 - 2), new Point(x1 + 2+textwidth, y2 - 2-textheight),RGB(255,255,0), FILLED,0,0);

yptheangel

import timeit
import time

start_time = timeit.default_timer()
# Using time module to create the delay, you can replce this line with your process
time.sleep(1)
end_time = timeit.default_timer()
elapsed_time = end_time - start_time
# Round the elapsed time to 2 decimal points
print("Elapsed time: {}".format(round(elapsed_time,2)))

yptheangel

import java.util.concurrent.TimeUnit;

public class JavaTimer{

     public static void main(String []args){
         
        long start_time =System.nanoTime();
       //Create a delay of 1 second or 1000milliseconds
        try{
            Thread.sleep(1000);

yptheangel

apply plugin: 'com.android.application'

android {
    compileSdkVersion 27
    buildToolsVersion "28.0.3"
    defaultConfig {
        applicationId "com.yptheangel.dl4jandroid.yolo_objdetection"
        minSdkVersion 24
        targetSdkVersion 24
        versionCode 1

yptheangel

package com.yptheangel.dl4jandroid.yolo_objdetection;

import android.app.Activity;
import android.os.AsyncTask;
import android.os.Bundle;
import android.os.Environment;
import android.util.Log;
import com.yptheangel.dl4jandroid.yolo_objdetection.utils.VOCLabelsAndroid;

import static android.os.Environment.getExternalStoragePublicDirectory;