why is CV_32FC1 not normalized to 0-1?
I needed to call an external CUDA library function that assumes the input data is CV_32FC1
. I'm working with data that comes in on a frame to frame basis, in RGBA, but at this point in time the data is already on the GPU. Instead of downloading an image to use OpenCV to convert, I figured I'd just do it myself. The most related question I could find was this SO post asking about the difference between CV_32F
and CV_32FC1
. The original function I wrote
/// will normalize to [0, 1] then use sRGB conversion to return single float gray
inline __host__ __device__
float rgbaToGray(const uchar4 &src) {
static constexpr float Wr = 0.2126f;
static constexpr float Wg = 0.7152f;
static constexpr float Wb = 0.0722f;
static constexpr float inv255 = 1.0f / 255.0f;
float r = Wr * ((float) src.x) * inv255;
float g = Wg * ((float) src.y) * inv255;
float b = Wb * ((float) src.z) * inv255;
return r + g + b;
}
as it turns out, dividing by 255.0f
was the fatal flaw. What are the assumptions made about the CV_32FC1
data type? Typically when I think about floating point color values, I assume they are in the range [0, 1]
(this is the expectation for OpenGL at least).
I couldn't really find any explicit documentation on what the value ranges are, do such expectations exist in OpenCV? For example, if I wanted to use CV_32FC3
for RGB values, do these values need to be in [0, 1]
?
Thank you for any guidance on what the OpenCV assumptions about image values are. The main reason I was avoiding using OpenCV to do anything directly was because
- The data was already on the GPU, and I'm not assuming users of the code have the CUDA backend for OpenCV installed.
- My understanding is OpenCV demands column-major BGRA storage. My data comes in from the device as row-major RGBA.