wehub-resource-sync
121 lines
4.5 KiB
Python
121 lines
4.5 KiB
Python
import sys
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import unittest
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from pathlib import Path
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import numpy as np
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sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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from moviepy import ImageClip
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from app.models.schema import VideoTransitionMode
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from app.services.utils import video_effects
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def _gradient_clip(width=64, height=48, duration=1.0):
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"""创建非均匀渐变画面，确保缩放前后的像素差异可以被可靠检测。"""
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x = np.linspace(0, 255, width, dtype=np.uint8)
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y = np.linspace(0, 255, height, dtype=np.uint8)
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frame = np.stack(np.meshgrid(x, y), axis=-1).sum(axis=-1) % 256
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rgb = np.stack([frame] * 3, axis=-1).astype(np.uint8)
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return ImageClip(rgb).with_duration(duration)
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def _detail_frame(width=128, height=96):
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"""创建包含高频细节的 RGB 帧，用于观察亚像素缩放是否连续响应。"""
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x = np.arange(width, dtype=np.int16)
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y = np.arange(height, dtype=np.int16)[:, None]
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return np.stack(
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(
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(x + y) % 256,
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(3 * x + y) % 256,
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(x + 3 * y) % 256,
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),
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axis=-1,
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).astype(np.uint8)
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class TestZoomTransitions(unittest.TestCase):
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def test_schema_has_zoom_members(self):
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self.assertEqual(VideoTransitionMode.zoom_in.value, "ZoomIn")
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self.assertEqual(VideoTransitionMode.zoom_out.value, "ZoomOut")
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def test_zoomin_preserves_geometry_and_zooms_over_time(self):
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clip = _gradient_clip()
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zoomed = video_effects.zoomin_transition(clip, 1)
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self.addCleanup(zoomed.close)
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self.addCleanup(clip.close)
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self.assertEqual(zoomed.size, clip.size)
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self.assertEqual(zoomed.duration, clip.duration)
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first = zoomed.get_frame(0)
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last = zoomed.get_frame(clip.duration - 0.01)
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original = clip.get_frame(0)
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self.assertEqual(first.shape, original.shape)
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self.assertEqual(first.dtype, np.uint8)
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# 放大从 1 倍开始，因此首帧应与原始画面保持一致。
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np.testing.assert_allclose(first, original, atol=2)
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# 末帧来自中心裁剪并放大后的区域，应与原始画面存在明显差异。
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self.assertGreater(np.abs(last.astype(int) - original.astype(int)).max(), 2)
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def test_zoomout_starts_zoomed_and_returns_to_source(self):
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clip = _gradient_clip()
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zoomed = video_effects.zoomout_transition(clip, 1)
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self.addCleanup(zoomed.close)
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self.addCleanup(clip.close)
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self.assertEqual(zoomed.size, clip.size)
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first = zoomed.get_frame(0)
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last = zoomed.get_frame(clip.duration)
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original = clip.get_frame(0)
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# 缩小的首帧为 1.2 倍画面，结束时精确回到原始比例。
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self.assertGreater(np.abs(first.astype(int) - original.astype(int)).max(), 2)
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np.testing.assert_allclose(last, original, atol=2)
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def test_zoom_frame_rejects_invalid_scale_factor(self):
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frame = np.zeros((8, 8, 3), dtype=np.uint8)
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with self.assertRaisesRegex(ValueError, "scale_factor"):
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video_effects._zoom_frame(frame, 0)
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def test_zoom_frame_responds_to_subpixel_scale_changes(self):
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frame = _detail_frame()
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first = video_effects._zoom_frame(frame, 1.1)
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second = video_effects._zoom_frame(frame, 1.1001)
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# 这两个比例在旧的整数裁剪算法中会落入相同裁剪尺寸，产生完全相同的帧，
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# 随后在跨过整数边界时突然跳变。亚像素采样应当能响应这种微小比例变化。
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self.assertGreater(np.count_nonzero(first != second), 0)
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self.assertLessEqual(
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np.abs(first.astype(np.int16) - second.astype(np.int16)).max(),
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1,
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)
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def test_zoom_frame_keeps_center_stable_for_odd_resolution(self):
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width, height = 59, 75
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center_x, center_y = width // 2, height // 2
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x = np.arange(width, dtype=np.int16) - center_x
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y = np.arange(height, dtype=np.int16)[:, None] - center_y
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radial = np.clip(x**2 + y**2, 0, 255).astype(np.uint8)
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frame = np.stack((radial, radial, radial), axis=-1)
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zoomed = video_effects._zoom_frame(frame, 1.2)
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self.assertEqual(zoomed.shape, frame.shape)
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self.assertEqual(zoomed.dtype, frame.dtype)
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# 奇数宽高只有一个精确中心像素，缩放后该像素不应发生横向或纵向漂移。
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np.testing.assert_allclose(
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zoomed[center_y, center_x],
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frame[center_y, center_x],
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atol=1,
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)
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if __name__ == "__main__":
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unittest.main()
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