Tag: opencv

Template Matching on Images using OpenCvSharp

- by Pupli 
//read image
// var refMat = new Mat("001f.png", ImreadModes.Unchanged);
// var tplMat = new Mat("001.png", ImreadModes.Unchanged);
using (Mat refMat = new Mat("001f.png", ImreadModes.Unchanged))
using (Mat tplMat = new Mat("001.png", ImreadModes.Unchanged))
using (Mat res = new Mat(refMat.Rows - tplMat.Rows + 1, refMat.Cols - tplMat.Cols + 1, MatType.CV_32FC1))
{
    //Convert input images to gray
    Mat gref = refMat.CvtColor(ColorConversionCodes.BGR2GRAY);
    Mat gtpl = tplMat.CvtColor(ColorConversionCodes.BGR2GRAY);

    Cv2.MatchTemplate(gref, gtpl, res, TemplateMatchModes.CCoeffNormed);
    Cv2.Threshold(res, res, 0.8, 1.0, ThresholdTypes.Tozero);

    while (true)
    {
        double minval, maxval, threshold = 0.8;
        Point minloc, maxloc;
        Cv2.MinMaxLoc(res, out minval, out maxval, out minloc, out maxloc);

        if (maxval >= threshold)
        {
            //draw a rectangle of the matching area
            Rect r = new Rect(new Point(maxloc.X, maxloc.Y), new Size(tplMat.Width, tplMat.Height));
            Cv2.Rectangle(refMat, r, Scalar.Red, 2);

            //debug
            String msg =
                $"MinVal={minval.ToString()} MaxVal={maxval.ToString()} MinLoc={minloc.ToString()} MaxLoc={maxloc.ToString()} Rect={r.ToString()}";
            Console.WriteLine(msg);

            //fill in the res mat so you don't find the same area again in the minmaxloc
            //Rect outRect;
            //Cv2.FloodFill(res, maxloc, new Scalar(0), out outRect, new Scalar(0.1), new Scalar(1.0), FloodFillFlags.Link4);
            Cv2.FloodFill(res, maxloc, new Scalar(0));
        }
        else
        {
            break;
        }
    }
}

 

Capture and Save IP Camera in Python OpenCV

- by Pupli 
import cv2

#print("Before URL")
cap = cv2.VideoCapture('rtsp://admin@192.168.10.29:554/cam/realmonitor?channel=1&subtype=1')
#print("After URL")

(grabbed, frame) = cap.read()
fshape = frame.shape
fheight = fshape[0]
fwidth = fshape[1]
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi',fourcc, 20.0, (fwidth,fheight))

while True:

    #print('About to start the Read command')
    ret, frame = cap.read()
    #print('About to show frame of Video.')
    cv2.imshow("Capturing",frame)
    #print('Running..')

    out.write(frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

References
https://pupli.net/2021/01/access-ip-camera-in-python-opencv/
https://stackoverflow.com/questions/29317262/opencv-video-saving-in-python

Access IP Camera in Python OpenCV

- by Pupli 
import cv2

#print("Before URL")
cap = cv2.VideoCapture('rtsp://admin:123456@192.168.1.216/H264?ch=1&subtype=0')
#print("After URL")

while True:

    #print('About to start the Read command')
    ret, frame = cap.read()
    #print('About to show frame of Video.')
    cv2.imshow("Capturing",frame)
    #print('Running..')

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

References
https://stackoverflow.com/questions/49978705/access-ip-camera-in-python-opencv
https://dahuawiki.com/Remote_Access/RTSP_via_VLC

Draw a rectangle around a region of interest in OpenCV Python

- by Pupli 
# Python program to explain cv2.rectangle() method 

# importing cv2 
import cv2 

# path 
path = r'C:\Users\Rajnish\Desktop\geeksforgeeks\geeks.png'

# Reading an image in default mode 
image = cv2.imread(path) 

# Window name in which image is displayed 
window_name = 'Image'

# Start coordinate, here (5, 5) 
# represents the top left corner of rectangle 
start_point = (5, 5) 

# Ending coordinate, here (220, 220) 
# represents the bottom right corner of rectangle 
end_point = (220, 220) 

# Blue color in BGR 
color = (255, 0, 0) 

# Line thickness of 2 px 
thickness = 2

# Using cv2.rectangle() method 
# Draw a rectangle with blue line borders of thickness of 2 px 
image = cv2.rectangle(image, start_point, end_point, color, thickness) 

# Displaying the image 
cv2.imshow(window_name, image) 
k = cv2.waitKey(0) # 0==wait forever

References
https://www.geeksforgeeks.org/python-opencv-cv2-rectangle-method/
https://stackoverflow.com/questions/23720875/how-to-draw-a-rectangle-around-a-region-of-interest-in-python

Template Matching using OpenCV Python

- by Pupli 
image_gray: np.ndarray
TM_METHOD=cv2.TM_CCOEFF_NORMED

def __init__(self):
    self.take_screenshot()

def take_screenshot(self):
    user32 = ctypes.windll.user32
    user32.SetProcessDPIAware()
    image = ImageGrab.grab()
    # save on file
    # image.save('screenshot.jpg', format='JPEG', quality=20)

    # load image from memory
    image_rgb = np.array(image)

    # load from file
    # image_rgb=cv2.imread('screenshot.jpg')
    self.image_gray = cv2.cvtColor(image_rgb, cv2.COLOR_BGR2GRAY)

@staticmethod
def save_screenshot():
    user32 = ctypes.windll.user32
    user32.SetProcessDPIAware()
    image = ImageGrab.grab()
    image.save("screenshot.jpg")

def template_available(self, template_path: str, threshold=0.9):

    # self.take_screenshot()

    template = cv2.imread(template_path, 0)
    # w, h = template.shape[::-1]

    res = cv2.matchTemplate(self.image_gray, template, self.TM_METHOD)
    loc = np.where(res >= threshold)

    if len(loc[0]) == 0 & len(loc[1]) == 0:
        return False
    else:
        print("template_available : " + template_path)
        return True

def template_count(self, template_path: str, threshold=0.9):

    # self.take_screenshot()

    template = cv2.imread(template_path, 0)
    # w, h = template.shape[::-1]

    res = cv2.matchTemplate(self.image_gray, template, self.TM_METHOD)
    loc = np.where(res >= threshold)

    return len(loc[0])

def template_location(self, template_path: str, threshold=0.9):

    self.take_screenshot()

    template = cv2.imread(template_path, 0)
    w, h = template.shape[::-1]

    res = cv2.matchTemplate(self.image_gray, template, self.TM_METHOD)
    loc = np.where(res >= threshold)

    if len(loc[0]) == 0 & len(loc[1]) == 0:
        return None
    else:
        click_y = loc[0][0] + h / 2
        click_x = loc[1][0] + w / 2

        return click_x, click_y

def move_mouse_to_template(self, template_path: str):
    loc = self.template_location(template_path)

    if loc is not None:
        click_x = loc[0]
        click_y = loc[1]
        pyautogui.moveTo(click_x, click_y)

def click_template(self, template_path: str, threshold=0.9):
    loc = self.template_location(template_path, threshold)

    if loc is not None:
        click_x = loc[0]
        click_y = loc[1]
        pyautogui.click(click_x, click_y)
        pyautogui.FAILSAFE = False
        pyautogui.moveTo(0, 0)
        print("click_template : " + template_path)
        return True

    return False

@staticmethod
def scroll_mouse(value=10):
    pyautogui.scroll(value)
    pyautogui.FAILSAFE = False
    pyautogui.moveTo(0, 0)

@staticmethod
def get_template_path(template: str):
    template_name = f"template{template}.jpg"
    template_path = os.path.join(os.getcwd(), 'templates', template_name)
    return template_path

 

Template Matching On Images C# using OpenCV

- by Pupli 
Image<Bgr, byte> Image1 = new Image<Bgr, byte>(Properties.Resources.Image1); //Your first image
        Image<Bgr, byte> Image2 = new Image<Bgr, byte>(Properties.Resources.Image2); //Your second image

        double Threshold = 0.8; //set it to a decimal value between 0 and 1.00, 1.00 meaning that the images must be identical

        Image<Gray, float> Matches = Image1.MatchTemplate(Image2, TemplateMatchingType.CcoeffNormed);

        for (int y = 0; y < Matches.Data.GetLength(0); y++)
        {
            for (int x = 0; x < Matches.Data.GetLength(1); x++)
            {
                 if (Matches.Data[y, x, 0] >= Threshold) //Check if its a valid match
                 {
                     //Image2 found within Image1
                 }
            }
        }

References
https://stackoverflow.com/questions/39570033/template-matching-on-images-c-sharp