2016-03-27 15:39:12 -0600 | commented question | Faster RGB to Grey conversion Python. @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()) |
2016-03-26 14:36:30 -0600 | commented question | Faster RGB to Grey conversion Python. @FooBar 720X576 |
2016-03-26 12:10:22 -0600 | commented question | Faster RGB to Grey conversion Python. 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 |
2016-03-26 11:48:06 -0600 | asked a question | Faster RGB to Grey conversion Python. 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. |
2016-03-09 02:49:21 -0600 | commented answer | Determine a piece of image is in large image, if there - how much Percentage Thanks @Tetragramm |
2016-03-06 04:09:28 -0600 | received badge | ● Supporter (source) |
2016-03-06 04:03:16 -0600 | commented answer | Determine a piece of image is in large image, if there - how much Percentage Thanks for your replay @Tetragramm. Can you please give me an example. |
2016-03-06 01:13:24 -0600 | asked a question | Determine a piece of image is in large image, if there - how much Percentage 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. |
2016-02-19 23:48:04 -0600 | asked a question | Contour approximation. Avoid extra rectangle height Binary image When I draw rectangle it gives me rectangle with maximum height. I dont want to use
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. |
2016-02-17 01:09:12 -0600 | received badge | ● Enthusiast |
2016-01-27 13:45:07 -0600 | asked a question | Which is the best way to compare two images in python. Histogram or Image quality functions 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. |