Shahrukh Q's profile - activity

@FooBar Lenove thinkpad.

image = cv2.imread(path)

start_time = datetime.now()

grey = cv2.cvtcolor(image, cv2.COLORBRG2GREY)

end_time = date time.now() print((end_time-star t_time).total_seconds())

@FooBar 720X576

I just print time before and after this function. I am using windows, intel i5 processor. I did not enabled any optimization. And I did not complie. @berak

I am using "cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY)" to convert grey it is taking 0.801 seconds to convert. I am developing a real-time application where I convert RGB image to grey and perform operation but it is slow. Is there any faster way to convert.

Thanks.

Thanks @Tetragramm

Thanks for your replay @Tetragramm. Can you please give me an example.

I am trying to find a piece of image in large image. I used template matching it always give coordinate if image is there or not there. I want to find the percentage occurrence of piece of image in large image. In fast way.

Binary image When I draw rectangle it gives me rectangle with maximum height. I dont want to use

enter code here epsilon = 0.1*cv2.arcLength(contour_value, True) contour_value = cv2.approxPolyDP(contour_value, epsilon, True)

Can anyone tell me best way to iterate the image and remove below extra contour or give me a way to iterate contour and approximate it manually. Thanks.

I am new in opencv, I would like to know which is the best way to compare two images -- either image quality functions like ( MSE or SSIM ) or Histogram comparison.

I am honor for you answers. Thanks.