Hi nice video for leaning for color deduction. I want to know what is the logic to find color lower and upper hsv value without any tool. Can you share the easy logic to find that . Example for green how to find low and high
yeah same here no matter what values I pass in high and low I keep getting a black image as a result with rgb values 0, 0, 0 and I don't get it did you find a solution to it ? if so please let me know
@@Jbc1507 Is it though? Because saturation and value can only have a maximum number of 100 since they are percentage values but the variable 'high_red' has a saturation and value number of 255 and 255. I'm not sure what format the colours are in either. Anyone else know?
great video thanks a lot but I've an issue here no matter what ranges of colours I pass as high and low I keep getting a black image as a result and I don't really get why can anyone help me understand why this is happening (I am trying to block all colours except for black) but again I wrote the same code with the same values to make sure that the problem isn't with my ranges but the same result always pops up a black image with rgb = 0, 0, 0 and as I said I don't get it
Thank you for this video, have you an idea how i can detect white cracks in a white surface, but the saturation of the surface and cracks are not similar. thanks
Nice tutorial! Is there a way to detect all chosen colors on one screen sweep instead of repeating the operation for each of them? I'm talking about the inRange() and bitwise_and() parts, I ask for performance purposes
hi bro nice tutorial, i want to ask something, how if we want to add more color on it? lets say we want to add secondary color, like purple, maroon or something else? how is it?
Thanks for the video concepts, but here for me the jupyter notebook (where I use to develop these types of programs) gives an error after I finish the program, and to get around this it is good practice to destroy the images and data that will not be most used after the end of the program. After doing this, the error in my kernel stopped showing up. This destruction of data that will not be used after the end of the program can be done by the following lines at the end of the program and outside the loop and conditional: cap.release() cv2.destroyAllWindows() PS: Hope this is helpful to someone.
In this case, either you tune the parameters to detect correctly only the color you're focusing on, or probably this method is not good for your specific case. I recommend to watch this free crash course: Computer Vision Blueprint pysource.com/register-to-watch-the-computer-vision-blueprint-workshop/ where I talk about 5 different object detection methods and color detection is only one of them
Is there a reason red color in background picture is not visible? because similar thing happens when i try detecting color that are at distance , idk why?
It's not about the distance, but about its luminance. you can adjust the low and higher ranges to include also that color. check this video to understand better how to adjust the ranges in real time. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-SJCu1d4xakQ.html
Hello, It's simple. You can check the size of the mask. 1) You calculate the area of each mask, you can simply do that by counting the number of white pixels in the mask (check one of my video about finding dirrerences between two images to see how to do that). 2) Then you can define the if the size is above a certain number of pixel, the color is detected.
The values seem to be a subjective choice It would seem Pysource viewed a series of colours with different HSV parameters in Gimp. From his eyes, anything less than [161, 155, 84] does not resemble red
