| import cv2 |
| import numpy as np |
| import pytest |
|
|
| from videoclean.cli import _build_parser |
| from videoclean.inpainters import OpenCVInpainter, get_registry |
| from videoclean.inpainters.base import InpaintJob |
|
|
|
|
| def _video(path, frames=4, width=96, height=64): |
| writer = cv2.VideoWriter(str(path), cv2.VideoWriter_fourcc(*"mp4v"), 4, (width, height)) |
| for i in range(frames): |
| frame = np.full((height, width, 3), 30 + i * 5, dtype=np.uint8) |
| cv2.rectangle(frame, (60, 20), (78, 30), (255, 255, 255), -1) |
| writer.write(frame) |
| writer.release() |
|
|
|
|
| def test_registry_and_cli_options(): |
| assert "opencv" in get_registry().names() |
| assert isinstance(get_registry().create("opencv", method="ns"), OpenCVInpainter) |
| args = _build_parser().parse_args([ |
| "clean", "input.mp4", "--inpaint-method", "ns", |
| "--inpaint-radius", "5", "--inpaint-dilate", "2", |
| ]) |
| assert (args.inpaint_method, args.inpaint_radius, args.inpaint_dilate) == ( |
| "ns", 5.0, 2, |
| ) |
|
|
| def test_mask_validation_and_normalization(tmp_path): |
| inpainter = OpenCVInpainter() |
| base = dict(video_path="x.mp4", output_dir=str(tmp_path), fps=4, frame_count=1, width=8, height=6) |
| with pytest.raises(ValueError, match="no inpaintable"): |
| inpainter._prepare_mask(InpaintJob(mask=np.zeros((6, 8), np.float32), **base)) |
| mask = inpainter._prepare_mask(InpaintJob(mask=np.eye(6, 8, dtype=np.float32)[:, :, None], **base)) |
| assert mask.dtype == np.uint8 |
| assert set(np.unique(mask)) <= {0, 255} |
|
|
|
|
| def test_inpaints_all_frames_and_reports_progress(tmp_path): |
| source = tmp_path / "source.mp4" |
| _video(source) |
| reader = cv2.VideoCapture(str(source)) |
| mask = np.zeros((64, 96, 1), dtype=np.float32) |
| mask[20:31, 60:79] = 1 |
| progress = [] |
| metrics = {} |
| outcome = OpenCVInpainter(radius=3, dilate=1).inpaint(InpaintJob( |
| video_path=str(source), mask=mask, output_dir=str(tmp_path), fps=4, |
| frame_count=4, width=96, height=64, reader=reader, progress=lambda d, t: progress.append((d, t)), metrics=metrics, |
| output_suffix="clean", |
| )) |
| reader.release() |
| assert outcome.backend == "opencv" |
| assert progress[-1] == (4, 4) |
| assert "inpainting_s" in metrics |
| output = cv2.VideoCapture(outcome.output_path) |
| count = 0 |
| while output.read()[0]: |
| count += 1 |
| output.release() |
| assert count == 4 |
|
|
