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"""
Bilateral histogram.
"""
from bilateral_grid import bilateral_grid
from bilateral_grid_Adams2019 import bilateral_grid_Adams2019
# from bilateral_grid_Li2018 import bilateral_grid_Li2018
from bilateral_grid_Mullapudi2016 import bilateral_grid_Mullapudi2016
import halide.imageio
import numpy as np
import sys
import timeit
def main():
if len(sys.argv) < 4:
print(f"Usage: {sys.argv[0]} input.png output.png range_sigma")
print(f"e.g. {sys.argv[0]} input.png output.png 0.1 10")
sys.exit(1)
input_path = sys.argv[1]
r_sigma = float(sys.argv[2])
output_path = sys.argv[3]
timing_iterations = 10
print(f"Reading from {input_path} ...")
input_buf_u8 = halide.imageio.imread(input_path)
assert input_buf_u8.dtype == np.uint8
# Convert to float32
input_buf = input_buf_u8.astype(np.float32)
input_buf /= 255.0
output_buf = np.empty(input_buf.shape, dtype=input_buf.dtype)
tests = {
"Manual": bilateral_grid,
"Adams2019": bilateral_grid_Adams2019,
#
# TODO: Don't test the Li2018-autoscheduled version here;
# it schedules the histogram stage with compute_root(),
# which (for a 4MP input image) attempts to allocate 124GB (!)...
#
# "Li2018": bilateral_grid_Li2018,
#
"Mullapudi2016": bilateral_grid_Mullapudi2016,
}
for name, fn in tests.items():
print(f"Running {name}... ", end="")
t = timeit.Timer(lambda: fn(input_buf, r_sigma, output_buf))
avg_time_sec = t.timeit(number=timing_iterations) / timing_iterations
print("time: %fms" % (avg_time_sec * 1e3))
output_buf *= 255.0
output_buf_u8 = output_buf.astype(np.uint8)
print(f"Saving to {output_path} ...")
halide.imageio.imwrite(output_path, output_buf_u8)
print("Success!")
sys.exit(0)
if __name__ == "__main__":
main()
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