tests/test_A/test_frames.py

"""Tests for harness/A/frames.py -- uniform/selective frame sampling."""

import numpy as np
import pytest

from harness.A import frames as frame_sampling


def test_sample_frames_rejects_unknown_selection(tmp_path):
    video = tmp_path / "scene.mp4"
    video.write_bytes(b"not a real video")
    with pytest.raises(ValueError):
        frame_sampling.sample_frames(str(video), 8, "random")


def test_sample_frames_rejects_nonpositive_frame_count(tmp_path):
    video = tmp_path / "scene.mp4"
    video.write_bytes(b"not a real video")
    with pytest.raises(ValueError):
        frame_sampling.sample_frames(str(video), 0, "uniform")


def test_sample_frames_rejects_missing_video(tmp_path):
    with pytest.raises(FileNotFoundError):
        frame_sampling.sample_frames(str(tmp_path / "missing.mp4"), 8, "uniform")


def test_sample_frames_returns_pil_images_in_order(tmp_path, monkeypatch):
    video = tmp_path / "scene.mp4"
    video.write_bytes(b"not a real video")
    fake_frames = np.stack(
        [np.full((4, 4, 3), value, dtype=np.uint8) for value in (10, 20, 30)]
    )
    monkeypatch.setattr(
        frame_sampling,
        "_sample_video_frames",
        lambda path, count, selection: (fake_frames, np.array([0.0, 1.0, 2.0])),
    )

    class _UnreadableCapture:
        def get(self, prop):
            return 0.0

        def release(self):
            pass

    monkeypatch.setattr(
        frame_sampling.cv2, "VideoCapture", lambda path: _UnreadableCapture()
    )
    result, timestamps, indices = frame_sampling.sample_frames(str(video), 3, "uniform")
    assert len(result) == 3
    assert np.array(result[0])[0, 0, 0] == 10
    assert np.array(result[2])[0, 0, 0] == 30
    assert timestamps == [0.0, 1.0, 2.0]
    # fps falls back to 1.0 for the fake (unreadable) video, so index == round(t * 1.0) == t.
    assert indices == [0, 1, 2]


def test_sample_frames_derives_indices_from_real_fps(tmp_path, monkeypatch):
    video = tmp_path / "scene.mp4"
    video.write_bytes(b"not a real video")
    fake_frames = np.stack([np.full((2, 2, 3), 1, dtype=np.uint8)] * 3)
    monkeypatch.setattr(
        frame_sampling,
        "_sample_video_frames",
        lambda path, count, selection: (fake_frames, np.array([0.0, 0.5, 1.0])),
    )

    class _FakeCapture:
        def get(self, prop):
            return 30.0

        def release(self):
            pass

    monkeypatch.setattr(frame_sampling.cv2, "VideoCapture", lambda path: _FakeCapture())
    _, timestamps, indices = frame_sampling.sample_frames(str(video), 3, "uniform")
    assert timestamps == [0.0, 0.5, 1.0]
    assert indices == [0, 15, 30]