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# Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmocr.models.textrecog.preprocessor import (BasePreprocessor,
TPSPreprocessor)
def test_tps_preprocessor():
with pytest.raises(AssertionError):
TPSPreprocessor(num_fiducial=-1)
with pytest.raises(AssertionError):
TPSPreprocessor(img_size=32)
with pytest.raises(AssertionError):
TPSPreprocessor(rectified_img_size=100)
with pytest.raises(AssertionError):
TPSPreprocessor(num_img_channel='bgr')
tps_preprocessor = TPSPreprocessor(
num_fiducial=20,
img_size=(32, 100),
rectified_img_size=(32, 100),
num_img_channel=1)
tps_preprocessor.init_weights()
tps_preprocessor.train()
batch_img = torch.randn(1, 1, 32, 100)
processed = tps_preprocessor(batch_img)
assert processed.shape == torch.Size([1, 1, 32, 100])
def test_base_preprocessor():
preprocessor = BasePreprocessor()
preprocessor.init_weights()
preprocessor.train()
batch_img = torch.randn(1, 1, 32, 100)
processed = preprocessor(batch_img)
assert processed.shape == torch.Size([1, 1, 32, 100])
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