Edward Lance Lorilla

【VUE JS】Detecting an image 404 Show default image when image not found
【FLUTTER ANDROID STUDIO and IOS】Stream Radio
【PYTHON OPENCV】Object detection OpenCV DNN module using MobileNet SSD and caffe pre trained models
【GAMEMAKER】Weapon control select weapon with mouse wheel
device detection

【VUE JS】Detecting an image 404 Show default image when image not found

Posted: 03 May 2021 08:26 AM PDT

【FLUTTER ANDROID STUDIO and IOS】Stream Radio

Posted: 03 May 2021 08:22 AM PDT

import 'dart:async';


import 'package:flutter/material.dart';
import 'package:flutter_radio/flutter_radio.dart';

void main() {
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'Flutter Radio',
      home: RadioScreen(),
    );
  }
}

class RadioScreen extends StatefulWidget {
  @override
  _RadioScreenState createState() => _RadioScreenState();
}

class _RadioScreenState extends State<RadioScreen> {
  String url = "http://server-23.stream-server.nl:8438";

  bool isPlaying = false;
  bool isVisible = true;

  @override
  void initState() {
    super.initState();
    audioStart();
  }

  Future<void> audioStart() async {
    await FlutterRadio.audioStart();
    print('Audio start playing');
  }

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text("Radio App Demo"),
      ),
      body: Center(
        child: Container(
          width: double.infinity,
          color: Colors.blueGrey,
          child: Column(
            children: <Widget>[
              Expanded(
                flex: 7,
                child: Icon(
                  Icons.radio,
                  color: Colors.white,
                  size: 150.0,
                ),
              ),
              Expanded(
                flex: 2,
                child: Row(
                  mainAxisAlignment: MainAxisAlignment.center,
                  children: <Widget>[
                    FloatingActionButton(
                      child: Icon(
                        Icons.stop,
                        color: Colors.pink,
                      ),
                      onPressed: () {
                        FlutterRadio.stop();
                      },
                    ),
                    Container(
                      width: 10.0,
                    ),
                    FloatingActionButton(
                        child: isPlaying
                            ? Icon(
                          Icons.pause,
                          color: Colors.white,
                        )
                            : Icon(
                          Icons.play_arrow,
                          color: Colors.white,
                        ),
                        onPressed: () {
                          setState(() {
                            FlutterRadio.play(url: url);
                            isPlaying = !isPlaying;
                            isVisible = !isVisible;
                          });
                        }),
                    Container(
                      width: 10.0,
                    ),
                  ],
                ),
              ),
              SizedBox(
                height: 50,
              )
            ],
          ),
        ),
      ),
    );
  }
}

【PYTHON OPENCV】Object detection OpenCV DNN module using MobileNet SSD and caffe pre trained models

Posted: 03 May 2021 08:18 AM PDT

"""

Object detection using OpenCV DNN module using MobileNet-SSD and caffe pre-trained models MobileNetSSD_deploy.caffemodel:  https://drive.google.com/uc?export=download&id=0B3gersZ2cHIxRm5PMWRoTkdHdHc MobileNetSSD_deploy.prototxt  https://raw.githubusercontent.com/chuanqi305/MobileNet-SSD/daef68a6c2f5fbb8c88404266aa28180646d17e0/MobileNetSSD_deploy.prototxt """ # Import required packages:import cv2from matplotlib import pyplot as plt  def show_img_with_matplotlib(color_img, title, pos):    """Shows an image using matplotlib capabilities"""     img_RGB = color_img[:, :, ::-1]     ax = plt.subplot(1, 1, pos)    plt.imshow(img_RGB)    plt.title(title)    plt.axis('off')  # Load the serialized caffe model from disk:net = cv2.dnn.readNetFromCaffe("MobileNetSSD_deploy.prototxt", "MobileNetSSD_deploy.caffemodel") # Load input image:image = cv2.imread("object_detection_test_image.png") # Prepare labels of the network (20 class labels + background):class_names = {0: 'background', 1: 'aeroplane', 2: 'bicycle', 3: 'bird', 4: 'boat', 5: 'bottle', 6: 'bus', 7: 'car',               8: 'cat', 9: 'chair', 10: 'cow', 11: 'diningtable', 12: 'dog', 13: 'horse', 14: 'motorbike',               15: 'person', 16: 'pottedplant', 17: 'sheep', 18: 'sofa', 19: 'train', 20: 'tvmonitor'} # Create the blob with a size of (300,300), mean subtraction values (127.5, 127.5, 127.5):# and also a scalefactor of 0.007843:blob = cv2.dnn.blobFromImage(image, 0.007843, (300, 300), (127.5, 127.5, 127.5))print(blob.shape) # Feed the input blob to the network, perform inference and ghe the output:net.setInput(blob)detections = net.forward() # Get inference time:t, _ = net.getPerfProfile()print('Inference time: %.2f ms' % (t * 1000.0 / cv2.getTickFrequency())) # Size of frame resize (300x300)dim = 300 # Process all detections:for i in range(detections.shape[2]):    # Get the confidence of the prediction:    confidence = detections[0, 0, i, 2]     # Filter predictions by confidence:    if confidence > 0.1:        # Get the class label:        class_id = int(detections[0, 0, i, 1])         # Get the coordinates of the object location:        xLeftBottom = int(detections[0, 0, i, 3] * dim)        yLeftBottom = int(detections[0, 0, i, 4] * dim)        xRightTop = int(detections[0, 0, i, 5] * dim)        yRightTop = int(detections[0, 0, i, 6] * dim)         # Factor for scale to original size of frame        heightFactor = image.shape[0] / dim        widthFactor = image.shape[1] / dim         # Scale object detection to frame        xLeftBottom = int(widthFactor * xLeftBottom)        yLeftBottom = int(heightFactor * yLeftBottom)        xRightTop = int(widthFactor * xRightTop)        yRightTop = int(heightFactor * yRightTop)         # Draw rectangle:        cv2.rectangle(image, (xLeftBottom, yLeftBottom), (xRightTop, yRightTop), (0, 255, 0), 2)         # Draw label and confidence:        if class_id in class_names:            label = class_names[class_id] + ": " + str(confidence)            labelSize, baseLine = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 1, 2)            yLeftBottom = max(yLeftBottom, labelSize[1])            cv2.rectangle(image, (xLeftBottom, yLeftBottom - labelSize[1]),                          (xLeftBottom + labelSize[0], yLeftBottom + 0), (0, 255, 0), cv2.FILLED)            cv2.putText(image, label, (xLeftBottom, yLeftBottom), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2) # Create the dimensions of the figure and set title:fig = plt.figure(figsize=(14, 8))plt.suptitle("Object detection using OpenCV DNN module and MobileNet-SSD", fontsize=14, fontweight='bold')fig.patch.set_facecolor('silver') # Show the output imageshow_img_with_matplotlib(image, "MobileNet-SSD for object detection", 1) # Show the Figure:plt.show()

【GAMEMAKER】Weapon control select weapon with mouse wheel

Posted: 03 May 2021 08:14 AM PDT

Information about object: obj_player

Sprite: spr_idle_down
Solid: false
Visible: true
Depth: 0
Persistent: false
Parent:
Children:
Mask:

No Physics Object

Create Event:

execute code:

///set up
enum player_state {
    idle,
    up,
    down,
    left,
    right
    }

dir=player_state.down;
is_moving=false;
image_speed=0.5;

Step Event:

execute code:

///keypress code
if (keyboard_check(vk_left))
{
    dir=player_state.left;
    is_moving=true;
}
else
if (keyboard_check(vk_right))
{
    dir=player_state.right;
    is_moving=true;
}
else
if (keyboard_check(vk_up))
{
    dir=player_state.up;
    is_moving=true;
}
else
if (keyboard_check(vk_down))
{
    dir=player_state.down;
    is_moving=true;
}
else
{
    is_moving=false;
}

execute code:

///movement
if is_moving
{
    switch (dir)
    {
        case player_state.up:
        y -= 4;
        break;

        case player_state.down:
        y += 4;
        break;

        case player_state.left:
        x -= 4;
        break;
   
        case player_state.right:
        x += 4;
        break;
    }
}

execute code:

///animation
if is_moving
{
    switch (dir)
    {
        case player_state.up:
        sprite_index=spr_walk_up;
        break;

        case player_state.down:
        sprite_index=spr_walk_down;
        break;

        case player_state.left:
        sprite_index=spr_walk_left;
        break;
   
        case player_state.right:
        sprite_index=spr_walk_right;
        break;
    }
}
else
{
    switch (dir)
    {
        case player_state.up:
        sprite_index=spr_idle_up;
        break;

        case player_state.down:
        sprite_index=spr_idle_down;
        break;

        case player_state.left:
        sprite_index=spr_idle_left;
        break;
   
        case player_state.right:
        sprite_index=spr_idle_right;
        break;
    }
}

execute code:

///use weapon
if mouse_check_button_pressed(mb_left)
{
    if global.weapon[global.selected,2]>0
    {
        audio_play_sound(global.weapon[global.selected,4],1,false);
        global.weapon[global.selected,2]--;
    }
    else
    audio_play_sound(snd_no_ammo,1,false);
}

Collision Event with object obj_hook_crate:

execute code:

global.weapon[1,2]+=10;
with (other) instance_destroy();

Collision Event with object obj_cutlass_crate:

execute code:

global.weapon[2,2]+=10;
with (other) instance_destroy();

Collision Event with object obj_gun_crate:

execute code:

global.weapon[3,2]+=10;
with (other) instance_destroy();

Information about object: obj_hook_crate
Sprite: spr_hook_crate
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: 
Children: 
Mask: 

No Physics Object

Information about object: obj_cutlass_crate
Sprite: spr_cutlass_crate
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: 
Children: 
Mask: 

No Physics Object

Information about object: obj_gun_crate
Sprite: spr_gun_crate
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: 
Children: 
Mask: 

No Physics Object

Information about object: obj_hud
Sprite: spr_hud_bg
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: 
Children: 
Mask: 

No Physics Object

Create Event:
execute code:

///set up, inc array to hold data
global.weapon[1,1]="HOOK";
global.weapon[1,2]=20;
global.weapon[1,3]=spr_hook_hud;
global.weapon[1,4]=snd_hook;

global.weapon[2,1]="CUTLASS";
global.weapon[2,2]=10;
global.weapon[2,3]=spr_cutlass_hud
global.weapon[2,4]=snd_cutlass;

global.weapon[3,1]="GUN";
global.weapon[3,2]=40;
global.weapon[3,3]=spr_gun_hud;
global.weapon[3,4]=snd_gun;

//set selected weapon
global.selected=1;

Step Event:
execute code:

///select weapon with mouse wheel
if mouse_wheel_up()
{
    global.selected-=1;
    if global.selected==0 global.selected=3;
}

if mouse_wheel_down()
{
    global.selected+=1;
    if global.selected==4 global.selected=1;
}
Draw Event:
execute code:

///comment to prevent default drawing
Draw GUI Event:
execute code:

///draw hud
//set alpha at 50%
draw_set_alpha(0.5);

draw_sprite(spr_hud_bg,0, 0,550);//background

//set up text
draw_set_font(drawing_font);
draw_set_halign(fa_center);
draw_set_valign(fa_middle);

//draw data
for (var loop = 1; loop < 4; loop += 1)
{
    draw_text(200+100*loop,590,global.weapon[loop,1]);//name
    draw_text(200+100*loop,650,global.weapon[loop,2]);//amount
    draw_sprite(global.weapon[loop,3],0,200+100*loop,645);//sprite
    //draw border if selected
    if loop==global.selected draw_sprite(spr_show_selected,0,200+100*loop,645);
}


//reset alpha to normal
draw_set_alpha(1);

//info
draw_text(400,50,"Touch Crate To Pick Up#Middle Mouse Button Up / Down To Select#Left Mouse To Use");

device detection

Posted: 03 May 2021 05:55 AM PDT

var isMobile = false; //initiate as false

// device detection

|| /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(navigator.userAgent.substr(0,4))) {

isMobile = true;

}

e-techbytes

Tuesday, May 4, 2021

Edward Lance Lorilla

Edward Lance Lorilla

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