【VISUAL VB.NET】Screen Capture

 ' make sure that using System.IO; is included

Imports System.IO ' make sure that using System.Drawing.Imaging; is included Imports System.Drawing.Imaging Public Class Form1 Private tempfile As String = "C:\\Users\\Lorilla Family\\temp.jpg" Private Sub ScreanCapture() If Directory.Exists(Path.GetDirectoryName(tempfile)) Then pictureBox1.Image = Nothing File.Delete(tempfile) End If Dim bounds As Rectangle = Me.Bounds Using bitmap As New Bitmap(bounds.Width, bounds.Height) Using g As Graphics = Graphics.FromImage(bitmap) g.CopyFromScreen(New Point(bounds.Left, bounds.Top), Point.Empty, bounds.Size) End Using bitmap.Save(tempfile, ImageFormat.Jpeg) End Using End Sub Private Sub Form1_Load(sender As Object, e As EventArgs) Handles MyBase.Load End Sub Private Sub Button1_Click(sender As Object, e As EventArgs) Handles Button1.Click ScreanCapture() Dim fs As New FileStream(tempfile, FileMode.Open) ' pictureBox1.Image = new Bitmap(tempfile); PictureBox1.Image = New Bitmap(fs) fs.Close() End Sub End Class

【GAMEMAKER】Ship Mini Game

 Information about object: obj_bubble

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

No Physics Object

Step Event:

execute code:

image_xscale*=0.99;
image_yscale*=0.99;
if image_xscale<0.05 instance_destroy();

Information about object: obj_beam_1
Sprite: spr_beam_1
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: obj_collision_parent
Children: 
Mask: 

No Physics Object
Information about object: obj_beam_2
Sprite: spr_beam_2
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: obj_collision_parent
Children: 
Mask: 

No Physics Object

Information about object: obj_beam_3
Sprite: spr_beam_3
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: obj_collision_parent
Children: 
Mask: 

No Physics Object
Information about object: obj_beam_4
Sprite: spr_beam_4
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: obj_collision_parent
Children: 
Mask: 

No Physics Object

Information about object: obj_game_end
Sprite: spr_flag
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: 
Children: 
Mask: 

No Physics Object

Information about object: obj_collision_parent
Sprite: 
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: 

Children
obj_beam_1
obj_beam_2
obj_beam_3
obj_beam_4
obj_crate_floating
obj_crate_path
Mask: 


No Physics Object

Information about object: obj_crate_floating
Sprite: spr_crate
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: obj_collision_parent
Children: 
Mask: 

No Physics Object
Create Event:
execute code:

angle=0;//initial angle
sw=5;//for sine wave

Step Event:
execute code:

sw += 0.3;//for sin wave
angle= sin(sw) * 5;//for sin wave
image_angle=angle;

Information about object: obj_crate_path
Sprite: spr_crate
Solid: false
Visible: true
Depth: 
0
Persistent: false
Parent: obj_collision_parent
Children: 
Mask: 

No Physics Object
Create Event:
execute code:

angle=0;//initial angle
sw=5;//for sine wave
path_start(path_crate_1,3,path_action_continue,true);

Step Event:
execute code:

sw += 0.3;//for sin wave
angle= sin(sw) * 5;//for sin wave
image_angle=direction+angle;

【PYTHON OPENCV】Face detection using OpenCV DNN face detector feeding several images to the network

 """

Face detection using OpenCV DNN face detector when feeding several images to the network """ # Import required packages: import cv2 import numpy as np from 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(2, 2, pos) plt.imshow(img_RGB) plt.title(title) plt.axis('off') # Load pre-trained model: net = cv2.dnn.readNetFromCaffe("deploy.prototxt", "res10_300x300_ssd_iter_140000_fp16.caffemodel") # Load images and get the list of images: image = cv2.imread("face_test.png") image2 = cv2.imread("face_test2.jpg") images = [image.copy(), image2.copy()] # Call cv2.dnn.blobFromImages(): blob_images = cv2.dnn.blobFromImages(images, 1.0, (300, 300), [104., 117., 123.], False, False) # Set the blob as input and obtain the detections: net.setInput(blob_images) detections = net.forward() # Iterate over all detections: # We have to check the first element of each detection to know which image it belongs to: for i in range(0, detections.shape[2]): # First, we have to get the image the detection belongs to: img_id = int(detections[0, 0, i, 0]) # Get the confidence of this prediction: confidence = detections[0, 0, i, 2] # Filter out weak predictions: if confidence > 0.25: # Get the size of the current image: (h, w) = images[img_id].shape[:2] # Get the (x,y) coordinates of the detection: box = detections[0, 0, i, 3:7] * np.array([w, h, w, h]) (startX, startY, endX, endY) = box.astype("int") # Draw bounding box and probability: text = "{:.2f}%".format(confidence * 100) y = startY - 10 if startY - 10 > 10 else startY + 10 cv2.rectangle(images[img_id], (startX, startY), (endX, endY), (0, 0, 255), 2) cv2.putText(images[img_id], text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2) # Create the dimensions of the figure and set title: fig = plt.figure(figsize=(16, 8)) plt.suptitle("OpenCV DNN face detector when feeding several images", fontsize=14, fontweight='bold') fig.patch.set_facecolor('silver') # Show the input and the output images with the detections: show_img_with_matplotlib(image, "input img 1", 1) show_img_with_matplotlib(image2, "input img 2", 2) show_img_with_matplotlib(images[0], "output img 1", 3) show_img_with_matplotlib(images[1], "output img 2", 4) # Show the Figure: plt.show()

【VUE JS】Checking out with payment request API

【VISUAL VB.NET】Add and Remove Programs

 Public Class Form1

Dim fileArgs As String Dim path As String = "C:\Windows\System32\" Dim cmdProcess As Process = New Process() Private Sub Button1_Click(sender As Object, e As EventArgs) Handles Button1.Click fileArgs = "shell32.dll,Control_RunDLL appwiz.cpl,,0" cmdProcess.StartInfo.Arguments = fileArgs cmdProcess.StartInfo.WorkingDirectory = path cmdProcess.StartInfo.FileName = "RunDll32.exe" cmdProcess.Start() cmdProcess.WaitForExit() Me.Show() End Sub End Class