def test():
inst1 = np.random.rand(10, 10) * 100000.3 - 1000
inst2 = np.random.randint(-100000, 100000, (10, 10))
for inst in [inst1, inst2]:
rgb = encode_inst_id.id_to_rgb(inst)
recover = encode_inst_id.rgb_to_id(rgb)
mg()
assert (inst == recover).all()
def test_heatmap_to_pseudo_color(depth):
def _f(v):
return tuple(interpolate_or_clip(turbo_colormap_data, v))
vf = np.vectorize(_f)
with timeit("vf"):
color1 = np.concatenate([i[..., None] for i in vf(depth)], -1)
with timeit("heatmap_to_pseudo_color"):
color2 = heatmap_to_pseudo_color(depth)
mg()
assert (np.abs(color1 - color2) < 1 / 256).all()
show - color1
def test(cls):
inst0 = np.arange(-100, 10000)
inst1 = np.random.randint(-cls.max_denominator / 2,
cls.max_denominator / 2, (10000))
inst2 = np.float32(
np.linspace(-cls.max_denominator / 2, cls.max_denominator / 2,
10000))
inst3 = np.float32(np.random.rand(10000) * 10000.3 - 1000)
for inst in [inst0, inst1, inst2, inst3]:
boxx.tree - inst
for inst_id in inst.flatten():
rgb = encode_inst_id.id_to_rgb(inst_id).astype(np.float32)
# print(rgb, inst_id)
recover = encode_inst_id.rgb_to_id(rgb)
boxx.mg()
assert recover == inst_id, (inst_id, recover)
assert (encode_inst_id.rgb_to_id(np.float32(
[0, 0, 0])) == 0), "Check background should decode to 0"