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Bilinearly interpolate points from an image using NumPy or CuPy
def bilinear_interpolate(img, points, clipped_nan=True):
"""Bilinearly interpolate points from an image using NumPy or CuPy
Args:
img: Image of shape (Y, X) to interpolate from.
points: array of shape (2, N) of (y, x) coordinates
clipped_nan: If True, the value of coordinates outside the image shape
are set to nan. Otherwise they are clipped to the image edge.
Returns:
I: Array of bilinearly interpolated intensities
"""
y, x = points
x0 = np.floor(x).astype(np.int32)
x1 = x0 + 1
y0 = np.floor(y).astype(np.int32)
y1 = y0 + 1
x0_clip = np.clip(x0, 0, img.shape[1])
x1_clip = np.clip(x1, 0, img.shape[1])
y0_clip = np.clip(y0, 0, img.shape[0])
y1_clip = np.clip(y1, 0, img.shape[0])
Ia = img[y0_clip, x0_clip]
Ib = img[y1_clip, x0_clip]
Ic = img[y0_clip, x1_clip]
Id = img[y1_clip, x1_clip]
wa = (x1-x) * (y1-y)
wb = (x1-x) * (y-y0)
wc = (x-x0) * (y1-y)
wd = (x-x0) * (y-y0)
I = (wa*Ia + wb*Ib + wc*Ic + wd*Id)
if clipped_nan:
mask = (x0 != x0_clip) | (x1 != x1_clip) | (y0 != y0_clip) | (y1 != y1_clip)
I[mask] = np.nan
return I
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