def horn_schunck(stem, pat:str):
flist = getimgfiles(stem, pat)
for i in range(len(flist)-1):
fn1 = flist[i]
im1 = imageio.imread(fn1, as_gray=True)
# Iold = gaussian_filter(Iold,FILTER)
fn2 = flist[i+1]
im2 = imageio.imread(fn2, as_gray=True)
# Inew = gaussian_filter(Inew,FILTER)
U,V = HornSchunck(im1, im2, 1., 100)
compareGraphs(U,V, im2, fn=fn2.name)
return U,V
def horn_schunck(stem: Path, pat: str, alpha: float, Niter: int,
verbose: bool):
flist = getimgfiles(stem, pat)
for i in range(len(flist) - 1):
fn1 = flist[i]
im1 = imageio.imread(fn1, as_gray=True)
# Iold = gaussian_filter(Iold,FILTER)
fn2 = flist[i + 1]
im2 = imageio.imread(fn2, as_gray=True)
# Inew = gaussian_filter(Inew,FILTER)
U, V = HornSchunck(im1, im2, alpha=1.0, Niter=100)
compareGraphs(U, V, im2, fn=fn2.name)
return U, V
def gif_generator(path, filenames=[]):
"""Saves a sequence of images as a .gif
input:
path: str, folder path where the images are located. It is also where the gif is saved.
filenames: list[str], a list containing the file names. If not provided it will use all .png images in the
folder provided in path. The file names are assumed sorted.
output:
saves flow.gif in the folder provided in path.
"""
images = []
if filenames == []:
filenames = getimgfiles(path, "*.png")
for filename in tqdm(filenames, ncols=100, desc="GIFing"):
images.append(imageio.imread(filename))
imageio.mimsave(path + "/flow.gif", images)
def horn_schunck(stem, pat: str, save_to: str):
flist = getimgfiles(stem, pat)
for i in tqdm(range(len(flist) - 1), ncols=100, desc="HS flow"):
fn1 = flist[i]
im1 = imageio.imread(fn1, as_gray=False)
im1 = np.flip(im1, 0)
fn2 = flist[i + 1]
im2 = imageio.imread(fn2, as_gray=False)
im2 = np.flip(im2, 0)
U, V = HornSchunck(rgb2gray(im1), rgb2gray(im2), 1., 100)
path = save_to + "/" + fn2.name
compareGraphs(U, V, im2, fn=fn2.name, save=path)
return U, V
def lucas_kanade(stem, pat: str, kernel: int = 5, Nfilter: int = 7):
flist = getimgfiles(stem, pat)
# %% priming read
im1 = imageio.imread(flist[0], as_gray=True)
# %% evaluate the first frame's POI
X = im1.shape[1] // 16
Y = im1.shape[0] // 16
poi = getPOI(X, Y, kernel)
# % get the weights
W = gaussianWeight(kernel)
# %% loop over all images in directory
for i in range(1, len(flist)):
im2 = imageio.imread(flist[i], as_gray=True)
im2 = gaussian_filter(im2, Nfilter)
V = LucasKanade(im1, im2, kernel, poi, W)
compareGraphsLK(im1, im2, poi, V)
im1 = im2.copy()
def test_io():
flist = pof.getimgfiles(RDIR / 'data/box', 'box*')
print(flist)
def test_io():
flist = pof.getimgfiles(RDIR / "data/box", "box*")
assert len(flist) == 2
