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import os
import sys
import mock
import numpy as np
import pytest
# mock detection module
sys.modules["torchvision._C"] = mock.Mock()
import segmentation_models_pytorch as smp
def _test_preprocessing(inp, out, **params):
preprocessed_output = smp.encoders.preprocess_input(inp, **params)
assert np.allclose(preprocessed_output, out)
def test_mean():
inp = np.ones((32, 32, 3))
out = np.zeros((32, 32, 3))
mean = (1, 1, 1)
_test_preprocessing(inp, out, mean=mean)
def test_std():
inp = np.ones((32, 32, 3)) * 255
out = np.ones((32, 32, 3))
std = (255, 255, 255)
_test_preprocessing(inp, out, std=std)
def test_input_range():
inp = np.ones((32, 32, 3))
out = np.ones((32, 32, 3))
_test_preprocessing(inp, out, input_range=(0, 1))
_test_preprocessing(inp * 255, out, input_range=(0, 1))
_test_preprocessing(inp * 255, out * 255, input_range=(0, 255))
def test_input_space():
inp = np.stack([np.ones((32, 32)), np.zeros((32, 32))], axis=-1)
out = np.stack([np.zeros((32, 32)), np.ones((32, 32))], axis=-1)
_test_preprocessing(inp, out, input_space="BGR")
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