mirror of https://github.com/open-mmlab/mmocr.git
50 lines
1.1 KiB
Python
50 lines
1.1 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import pytest
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import torch
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from mmocr.models.textrecog.backbones import (ResNet31OCR, ShallowCNN,
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VeryDeepVgg)
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def test_resnet31_ocr_backbone():
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"""Test resnet backbone."""
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with pytest.raises(AssertionError):
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ResNet31OCR(2.5)
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with pytest.raises(AssertionError):
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ResNet31OCR(3, layers=5)
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with pytest.raises(AssertionError):
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ResNet31OCR(3, channels=5)
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# Test ResNet18 forward
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model = ResNet31OCR()
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model.init_weights()
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model.train()
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imgs = torch.randn(1, 3, 32, 160)
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feat = model(imgs)
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assert feat.shape == torch.Size([1, 512, 4, 40])
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def test_vgg_deep_vgg_ocr_backbone():
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model = VeryDeepVgg()
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model.init_weights()
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model.train()
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imgs = torch.randn(1, 3, 32, 160)
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feats = model(imgs)
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assert feats.shape == torch.Size([1, 512, 1, 41])
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def test_shallow_cnn_ocr_backbone():
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model = ShallowCNN()
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model.init_weights()
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model.train()
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imgs = torch.randn(1, 1, 32, 100)
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feat = model(imgs)
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assert feat.shape == torch.Size([1, 512, 8, 25])
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