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73 lines
2.6 KiB
Python
73 lines
2.6 KiB
Python
# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numpy as np
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import paddle
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import pytest
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from ppocr.postprocess.cls_postprocess import ClsPostProcess
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# Fixtures for common test inputs
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@pytest.fixture
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def preds_tensor():
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return paddle.to_tensor(np.array([[0.1, 0.7, 0.2], [0.3, 0.3, 0.4]]))
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@pytest.fixture
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def label_list():
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return {0: "class0", 1: "class1", 2: "class2"}
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# Parameterize tests to cover multiple scenarios
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@pytest.mark.parametrize(
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"label_list, expected",
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[
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({0: "class0", 1: "class1", 2: "class2"}, [("class1", 0.7), ("class2", 0.4)]),
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(None, [(1, 0.7), (2, 0.4)]),
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],
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)
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def test_cls_post_process_with_and_without_label_list(
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preds_tensor, label_list, expected
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):
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post_process = ClsPostProcess(label_list=label_list)
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result = post_process(preds_tensor)
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assert isinstance(result, list), "Result should be a list"
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assert result == expected, f"Expected {expected}, got {result}"
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# Test with a key in the prediction dictionary
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def test_cls_post_process_with_key(preds_tensor, label_list):
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preds_dict = {"key": preds_tensor}
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post_process = ClsPostProcess(label_list=label_list, key="key")
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result = post_process(preds_dict)
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expected = [("class1", 0.7), ("class2", 0.4)]
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assert isinstance(result, list), "Result should be a list"
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assert result == expected, f"Expected {expected}, got {result}"
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# Test with label input
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def test_cls_post_process_with_label(preds_tensor, label_list):
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labels = [2, 0]
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post_process = ClsPostProcess(label_list=label_list)
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result, label_result = post_process(preds_tensor, labels)
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expected_result = [("class1", 0.7), ("class2", 0.4)]
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expected_label_result = [("class2", 1.0), ("class0", 1.0)]
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assert isinstance(result, list), "Result should be a list"
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assert result == expected_result, f"Expected {expected_result}, got {result}"
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assert isinstance(label_result, list), "Label result should be a list"
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assert (
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label_result == expected_label_result
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), f"Expected {expected_label_result}, got {label_result}"
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