207 lines
6.5 KiB
Python
207 lines
6.5 KiB
Python
# -*- coding: utf-8 -*-
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"""
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video_split 单元测试
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"""
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import os
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import json
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from pathlib import Path
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import pytest
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# 确保 src 在 path 中
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import sys
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from doco.video_split import (
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hamming_distance,
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format_timestamp,
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build_b_manuscript,
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is_blank_frame,
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)
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class TestHammingDistance:
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def test_identical_strings(self):
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assert hamming_distance("abc", "abc") == 0
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def test_different_strings(self):
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assert hamming_distance("abc", "abd") == 1
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def test_different_length(self):
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# 长度不同时,返回较长字符串的长度
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assert hamming_distance("abc", "ab") == 3
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class TestFormatTimestamp:
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def test_zero(self):
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assert format_timestamp(0) == "0m0s"
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def test_seconds_only(self):
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assert format_timestamp(30000) == "0m30s" # 30秒
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def test_minutes_and_seconds(self):
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assert format_timestamp(90000) == "1m30s" # 1分30秒
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def test_longer(self):
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assert format_timestamp(3723000) == "62m3s" # 62分3秒
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class TestBuildBManuscript:
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def test_empty_keyframes(self):
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lines = build_b_manuscript([])
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assert lines == []
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def test_single_frame(self):
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keyframes = [
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{"timestamp_ms": 0, "ocr_text": "测试字幕"}
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]
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lines = build_b_manuscript(keyframes)
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assert len(lines) == 1
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assert "[0m0s]" in lines[0]
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assert "测试字幕" in lines[0]
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def test_duplicate_text_merged(self):
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"""相邻同文本应合并"""
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keyframes = [
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{"timestamp_ms": 0, "ocr_text": "相同"},
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{"timestamp_ms": 1000, "ocr_text": "相同"},
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{"timestamp_ms": 2000, "ocr_text": "不同"},
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]
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lines = build_b_manuscript(keyframes)
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assert len(lines) == 2
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def test_placeholder_skipped(self):
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"""OCR占位文本应跳过"""
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keyframes = [
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{"timestamp_ms": 0, "ocr_text": "[OCR待填充 frame=001.png]"},
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{"timestamp_ms": 1000, "ocr_text": "真实字幕"},
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]
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lines = build_b_manuscript(keyframes)
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assert len(lines) == 1
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assert "真实字幕" in lines[0]
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class TestKeyframesJson:
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"""验证 keyframes.json 输出格式"""
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def test_keyframe_structure(self, tmp_path):
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"""验证单个关键帧的 JSON 结构"""
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# 模拟关键帧数据
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kf = {
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"frame_index": 1,
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"timestamp_ms": 1000,
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"frame_image_path": str(tmp_path / "frame_0001.png"),
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"phash": "ff00aabb12345678",
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"ocr_text": "测试",
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}
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# 验证字段存在
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assert "frame_index" in kf
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assert "timestamp_ms" in kf
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assert "frame_image_path" in kf
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assert "phash" in kf
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assert "ocr_text" in kf
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def test_keyframes_json_output(self, tmp_path):
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"""验证完整 keyframes.json 输出"""
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frames_dir = tmp_path / "frames"
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frames_dir.mkdir()
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# 创建一个测试图片
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test_img = frames_dir / "frame_0001.png"
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test_img.write_bytes(b"fake_png_data")
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keyframes_data = {
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"video_path": str(tmp_path / "video.mp4"),
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"fps_sampled": 1,
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"phash_threshold": 8,
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"keyframes": [
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{
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"frame_index": 0,
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"timestamp_ms": 0,
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"frame_image_path": str(test_img),
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"phash": "abcd1234",
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"ocr_text": "首帧",
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}
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]
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}
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json_path = tmp_path / "keyframes.json"
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with open(json_path, "w", encoding="utf-8") as f:
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json.dump(keyframes_data, f, ensure_ascii=False, indent=2)
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# 验证可读
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with open(json_path, "r", encoding="utf-8") as f:
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loaded = json.load(f)
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assert loaded["fps_sampled"] == 1
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assert loaded["phash_threshold"] == 8
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assert len(loaded["keyframes"]) == 1
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assert loaded["keyframes"][0]["frame_index"] == 0
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class TestIsBlankFrame:
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"""is_blank_frame 双条件检测单元测试"""
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def test_pure_black_frame(self, tmp_path):
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"""全 0 纯黑图:max_brightness=0,white_ratio=0,is_blank=True"""
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from PIL import Image
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img_path = tmp_path / "black.png"
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img = Image.new("L", (100, 100), 0) # 全黑
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img.save(img_path)
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is_blank, white_ratio, max_brightness = is_blank_frame(img_path)
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assert is_blank is True
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assert max_brightness == 0
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assert white_ratio == 0.0
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def test_subtitle_frame(self, tmp_path):
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"""有少量白像素(亮度255,占~1%)的图:is_blank=False"""
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from PIL import Image
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import numpy as np
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img_path = tmp_path / "subtitle.png"
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arr = np.zeros((100, 100), dtype=np.uint8)
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# 1% 白像素(亮度255),其余黑(亮度0)
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arr[:10, :10] = 255 # 10×10=100/10000=1%
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img = Image.fromarray(arr, mode="L")
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img.save(img_path)
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is_blank, white_ratio, max_brightness = is_blank_frame(img_path)
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assert is_blank is False
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assert max_brightness == 255
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assert 0.005 <= white_ratio <= 0.02 # ~1%
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def test_max_brightness_ok_but_ratio_too_low(self, tmp_path):
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"""max_brightness>=240 但 white_ratio<0.005 → is_blank=True"""
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from PIL import Image
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import numpy as np
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img_path = tmp_path / "few_pixels.png"
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arr = np.zeros((100, 100), dtype=np.uint8)
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# 只有 0.1% 白像素(不够 0.5%),但 max_brightness=255
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arr[:10, :1] = 255
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img = Image.fromarray(arr, mode="L")
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img.save(img_path)
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is_blank, white_ratio, max_brightness = is_blank_frame(img_path)
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assert is_blank is True
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assert max_brightness == 255
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assert white_ratio < 0.005
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def test_ratio_ok_but_max_brightness_too_low(self, tmp_path):
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"""max_brightness<240 → 白像素计数全为0 → is_blank=True"""
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from PIL import Image
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import numpy as np
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img_path = tmp_path / "dim_pixels.png"
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arr = np.zeros((100, 100), dtype=np.uint8)
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# 1% 像素亮度=220(不满足阈值240),其余黑
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# is_blank_frame 用 arr > 240 统计白像素,220 全不满足 → white_ratio=0
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arr[:10, :10] = 220
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img = Image.fromarray(arr, mode="L")
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img.save(img_path)
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is_blank, white_ratio, max_brightness = is_blank_frame(img_path)
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assert is_blank is True
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assert max_brightness == 220
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assert white_ratio == 0.0
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