""" OCR 服务单元测试 TDD 测试用例 - 基于 DevelopmentPlan.md 的验收标准 验收标准： - 准确率 ≥ 95%（含复杂背景） """ import pytest from typing import Any # 导入待实现的模块（TDD 红灯阶段） # from app.services.ai.ocr import OCRService, OCRResult, OCRDetection class TestOCRService: """OCR 服务测试""" @pytest.mark.ai @pytest.mark.unit def test_ocr_service_initialization(self) -> None: """测试 OCR 服务初始化""" # TODO: 实现 OCR 服务 # service = OCRService() # assert service.is_ready() # assert service.model_name is not None pytest.skip("待实现：OCR 服务初始化") @pytest.mark.ai @pytest.mark.unit def test_ocr_extract_text_from_image(self) -> None: """测试从图片提取文字""" # TODO: 实现文字提取 # service = OCRService() # result = service.extract_text("tests/fixtures/images/text_sample.jpg") # # assert result.status == "success" # assert len(result.detections) > 0 pytest.skip("待实现：图片文字提取") @pytest.mark.ai @pytest.mark.unit def test_ocr_output_format(self) -> None: """测试 OCR 输出格式""" # TODO: 实现 OCR 服务 # service = OCRService() # result = service.extract_text("tests/fixtures/images/text_sample.jpg") # # # 验证输出结构 # assert hasattr(result, "detections") # assert hasattr(result, "full_text") # # # 验证 detection 结构 # for detection in result.detections: # assert hasattr(detection, "text") # assert hasattr(detection, "confidence") # assert hasattr(detection, "bbox") # assert len(detection.bbox) == 4 # [x1, y1, x2, y2] pytest.skip("待实现：OCR 输出格式") class TestOCRAccuracy: """OCR 准确率测试""" @pytest.mark.ai @pytest.mark.unit def test_ocr_accuracy_threshold(self) -> None: """ 测试 OCR 准确率阈值 验收标准：准确率 ≥ 95% """ # TODO: 使用标注测试集验证 # service = OCRService() # test_cases = load_ocr_labeled_dataset() # # correct = 0 # for case in test_cases: # result = service.extract_text(case["image_path"]) # if normalize_text(result.full_text) == normalize_text(case["ground_truth"]): # correct += 1 # # accuracy = correct / len(test_cases) # assert accuracy >= 0.95, f"准确率 {accuracy:.2%} 低于阈值 95%" pytest.skip("待实现：OCR 准确率测试") @pytest.mark.ai @pytest.mark.unit @pytest.mark.parametrize("background_type,expected_accuracy", [ ("simple_white", 0.99), # 简单白底 ("solid_color", 0.98), # 纯色背景 ("gradient", 0.95), # 渐变背景 ("complex_image", 0.90), # 复杂图片背景 ("video_frame", 0.90), # 视频帧 ]) def test_ocr_accuracy_by_background( self, background_type: str, expected_accuracy: float, ) -> None: """测试不同背景类型的 OCR 准确率""" # TODO: 实现分背景类型测试 # service = OCRService() # test_cases = load_ocr_test_set_by_background(background_type) # # accuracy = calculate_ocr_accuracy(service, test_cases) # assert accuracy >= expected_accuracy pytest.skip(f"待实现：{background_type} OCR 准确率测试") class TestOCRChinese: """中文 OCR 测试""" @pytest.mark.ai @pytest.mark.unit def test_simplified_chinese_recognition(self) -> None: """测试简体中文识别""" # TODO: 实现简体中文测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/simplified_chinese.jpg") # # assert "测试" in result.full_text pytest.skip("待实现：简体中文识别") @pytest.mark.ai @pytest.mark.unit def test_traditional_chinese_recognition(self) -> None: """测试繁体中文识别""" # TODO: 实现繁体中文测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/traditional_chinese.jpg") # # assert result.status == "success" pytest.skip("待实现：繁体中文识别") @pytest.mark.ai @pytest.mark.unit def test_mixed_chinese_english(self) -> None: """测试中英混合文字识别""" # TODO: 实现中英混合测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/mixed_cn_en.jpg") # # # 应能同时识别中英文 # assert result.status == "success" pytest.skip("待实现：中英混合识别") class TestOCRVideoFrame: """视频帧 OCR 测试""" @pytest.mark.ai @pytest.mark.unit def test_ocr_video_subtitle(self) -> None: """测试视频字幕识别""" # TODO: 实现字幕识别 # service = OCRService() # result = service.extract_text("tests/fixtures/images/video_subtitle.jpg") # # assert len(result.detections) > 0 # # 字幕通常在画面下方 # subtitle_detection = result.detections[0] # assert subtitle_detection.bbox[1] > 0.6 # y 坐标在下半部分 pytest.skip("待实现：视频字幕识别") @pytest.mark.ai @pytest.mark.unit def test_ocr_watermark_detection(self) -> None: """测试水印文字识别""" # TODO: 实现水印识别 # service = OCRService() # result = service.extract_text("tests/fixtures/images/with_watermark.jpg") # # # 应能检测到水印文字 # watermark_found = any( # d.is_watermark for d in result.detections # ) # assert watermark_found or len(result.detections) > 0 pytest.skip("待实现：水印文字识别") @pytest.mark.ai @pytest.mark.unit def test_ocr_batch_video_frames(self) -> None: """测试批量视频帧 OCR""" # TODO: 实现批量处理 # service = OCRService() # frame_paths = [ # f"tests/fixtures/images/frame_{i}.jpg" # for i in range(10) # ] # # results = service.batch_extract(frame_paths) # # assert len(results) == 10 # assert all(r.status == "success" for r in results) pytest.skip("待实现：批量视频帧 OCR") class TestOCRSpecialCases: """OCR 特殊情况测试""" @pytest.mark.ai @pytest.mark.unit def test_rotated_text(self) -> None: """测试旋转文字识别""" # TODO: 实现旋转文字测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/rotated_text.jpg") # # assert result.status == "success" # assert len(result.detections) > 0 pytest.skip("待实现：旋转文字识别") @pytest.mark.ai @pytest.mark.unit def test_vertical_text(self) -> None: """测试竖排文字识别""" # TODO: 实现竖排文字测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/vertical_text.jpg") # # assert result.status == "success" pytest.skip("待实现：竖排文字识别") @pytest.mark.ai @pytest.mark.unit def test_artistic_font(self) -> None: """测试艺术字体识别""" # TODO: 实现艺术字体测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/artistic_font.jpg") # # # 艺术字体准确率可能较低，但应能识别 # assert result.status == "success" pytest.skip("待实现：艺术字体识别") @pytest.mark.ai @pytest.mark.unit def test_no_text_image(self) -> None: """测试无文字图片""" # TODO: 实现无文字测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/no_text.jpg") # # assert result.status == "success" # assert len(result.detections) == 0 # assert result.full_text == "" pytest.skip("待实现：无文字图片处理") @pytest.mark.ai @pytest.mark.unit def test_blurry_text(self) -> None: """测试模糊文字识别""" # TODO: 实现模糊文字测试 # service = OCRService() # result = service.extract_text("tests/fixtures/images/blurry_text.jpg") # # # 模糊文字可能识别失败或置信度低 # if result.status == "success" and len(result.detections) > 0: # avg_confidence = sum(d.confidence for d in result.detections) / len(result.detections) # assert avg_confidence < 0.9 # 置信度应较低 pytest.skip("待实现：模糊文字识别") class TestOCRPerformance: """OCR 性能测试""" @pytest.mark.ai @pytest.mark.performance def test_ocr_processing_speed(self) -> None: """测试 OCR 处理速度""" # TODO: 实现性能测试 # import time # # service = OCRService() # # # 标准 1080p 图片 # start_time = time.time() # result = service.extract_text("tests/fixtures/images/1080p_sample.jpg") # processing_time = time.time() - start_time # # # 单张图片处理应 < 1 秒 # assert processing_time < 1.0, \ # f"处理时间 {processing_time:.2f}s 超过阈值 1s" pytest.skip("待实现：OCR 处理速度测试") @pytest.mark.ai @pytest.mark.performance def test_ocr_batch_processing_speed(self) -> None: """测试批量 OCR 处理速度""" # TODO: 实现批量性能测试 # import time # # service = OCRService() # frame_paths = [ # f"tests/fixtures/images/frame_{i}.jpg" # for i in range(30) # 30 帧 = 1 秒视频 @ 30fps # ] # # start_time = time.time() # results = service.batch_extract(frame_paths) # processing_time = time.time() - start_time # # # 30 帧应在 5 秒内处理完成 # assert processing_time < 5.0 pytest.skip("待实现：批量 OCR 处理速度测试")