import os import sys import numpy as np import paddle import pytest current_dir = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.abspath(os.path.join(current_dir, ".."))) from ppocr.postprocess.cls_postprocess import ClsPostProcess # Fixtures for common test inputs @pytest.fixture def preds_tensor(): return paddle.to_tensor(np.array([[0.1, 0.7, 0.2], [0.3, 0.3, 0.4]])) @pytest.fixture def label_list(): return {0: "class0", 1: "class1", 2: "class2"} # Parameterize tests to cover multiple scenarios @pytest.mark.parametrize( "label_list, expected", [ ({0: "class0", 1: "class1", 2: "class2"}, [("class1", 0.7), ("class2", 0.4)]), (None, [(1, 0.7), (2, 0.4)]), ], ) def test_cls_post_process_with_and_without_label_list( preds_tensor, label_list, expected ): post_process = ClsPostProcess(label_list=label_list) result = post_process(preds_tensor) assert isinstance(result, list), "Result should be a list" assert result == expected, f"Expected {expected}, got {result}" # Test with a key in the prediction dictionary def test_cls_post_process_with_key(preds_tensor, label_list): preds_dict = {"key": preds_tensor} post_process = ClsPostProcess(label_list=label_list, key="key") result = post_process(preds_dict) expected = [("class1", 0.7), ("class2", 0.4)] assert isinstance(result, list), "Result should be a list" assert result == expected, f"Expected {expected}, got {result}" # Test with label input def test_cls_post_process_with_label(preds_tensor, label_list): labels = [2, 0] post_process = ClsPostProcess(label_list=label_list) result, label_result = post_process(preds_tensor, labels) expected_result = [("class1", 0.7), ("class2", 0.4)] expected_label_result = [("class2", 1.0), ("class0", 1.0)] assert isinstance(result, list), "Result should be a list" assert result == expected_result, f"Expected {expected_result}, got {result}" assert isinstance(label_result, list), "Label result should be a list" assert ( label_result == expected_label_result ), f"Expected {expected_label_result}, got {label_result}"