def test_text2png(self):
""" Tests creation of an image array from a text expression.
Covers the text2png and text2array functions.
"""
text2png("TEST", fontsize=1000)
assert os.path.exists("TEST.png")
os.remove("TEST.png")
def text2array(text, fontsize=100):
"""
Renders inputted text, and returns array representation.
Inputs:
text (string) - text to render
Returns: A (ndarray) - 2D numpy array of rendered text
"""
text2png(text, fn="_text", fontsize=fontsize)
A = plt.imread("_text.png")[:, :, :3].mean(axis=2)
os.remove("_text.png")
return A.max() - A
def text2array(text, fontsize=100):
"""
Renders inputted text, and returns array representation.
Inputs:
text (string) - text to render
Returns: A (ndarray) - 2D numpy array of rendered text
"""
text2png(text, fn="_text", fontsize=fontsize)
A = plt.imread("_text.png")[:, :, :3].mean(axis=2)
os.remove("_text.png")
return A.max() - A
Some quick examples
"""
A = lena() # load Lena image, shrink in half
A = gaussian_filter(A, 1) # smoothing
numpy2stl(A, "examples/Lena.stl", scale=0.1, solid=False)
A = 256 * imread("examples/example_data/NASA.png")
A = A[:, :, 2] + 1.0*A[:,:, 0] # Compose RGBA channels to give depth
A = gaussian_filter(A, 1) # smoothing
numpy2stl(A, "examples/NASA.stl", scale=0.05, mask_val=5., solid=True)
A = 256 * imread("examples/example_data/openmdao.png")
A = A[:, :, 0] + 1.*A[:,:, 3] # Compose some elements from RGBA to give depth
A = gaussian_filter(A, 2) # smoothing
numpy2stl(A, "examples/OpenMDAO-logo.stl",
scale=0.05, mask_val=1., min_thickness_percent=0.005, solid=True)
text = ("$\oint_{\Gamma} (A\, dx + B\, dy) = \iint_{U} \left(\\frac{\partial "
"B}{\partial x} - \\frac{\partial A}{\partial y}\\right)\ dxdy$ \n\n "
"$\\frac{\partial \\rho}{\partial t} + \\frac{\partial}{\partial x_j}"
"\left[ \\rho u_j \\right] = 0$")
# save png
text2png(text, "examples/Greens-Theorem_Navier-Stokes", fontsize=50)
# read from rendered png
A = 256 * imread("examples/Greens-Theorem_Navier-Stokes.png")
A = A.mean(axis=2) # grayscale projection
A = gaussian_filter(A.max() - A, 1.0)
numpy2stl(A, "examples/Greens-Theorem_Navier-Stokes.stl", scale=0.15,
mask_val=5.)
