I'm confused why my canvas class produce only 255 colors that is colors that are the pure red in this case.
Although my code specifies darker tones of red for the colors of the different pixels, the resulting image linked below the code shows the same color for each pixel.
Code to reproduce.
class Canvas():
def __init__(self, x, y):
self.x = x
self.y = y
self.pixels = np.zeros((y,x,3))
def _center2pixel(self, x, y):
return (self.y//2 - y, self.x//2 + x)
def write_pixel(self, x, y, color):
x,y = self._center2pixel(x,y)
self.pixels[x,y] = color
def show(self):
plt.imshow(self.pixels, vmin=0, vmax=255)
plt.show()
canvas = Canvas(10,10)
canvas.write_pixel(0,0,np.array([255,0,0])*0.1)
canvas.write_pixel(1,0,np.array([255,0,0]))
canvas.write_pixel(2,0,np.array([10,0,0]))
canvas.write_pixel(3,0,np.array([25.5,0,0]))
canvas.show()
4 pixels with the same color value although they were designed to have different color values
Are you able to help me resolve this? What am I doing wrong?
Moreover, I get a warning that it has clipped the input, and that it should be between 0 and 255 - which it is.
I tried to specify different colors, but the same color shows up on the plot.
All of your arrays contain floats, which is the numpy default. When you use floats for RGB, they must be between 0 and 1, which is exactly what the error message tells you. Your values are all greater than 1, and so are fully saturated.
You have two choices. Either use dtype=np.uint8 to turn your colors into integers, or change your range to [0,1]:
canvas.write_pixel(0,0,np.array([1,0,0])*0.1)
canvas.write_pixel(1,0,np.array([1,0,0]))
canvas.write_pixel(2,0,np.array([0.04,0,0]))
canvas.write_pixel(3,0,np.array([0.1,0,0]))