refactor: remove opencv dependency

pyproject.toml

@@ -273,7 +273,6 @@ exclude = '''(?x)(
     tests/core/test_Core.py |
     tests/data/test_multi_view_collate.py |
     tests/data/test_data_collate.py |
-    tests/data/test_VideoDataset.py |
     tests/data/test_LightlySubset.py |
     tests/data/test_LightlyDataset.py |
     tests/embedding/test_callbacks.py |

tests/data/test_VideoDataset.py

@@ -1,14 +1,15 @@
+from __future__ import annotations
+
 import contextlib
 import io
 import os
 import shutil
 import tempfile
 import unittest
 from fractions import Fraction
-from typing import List
+from typing import Any
 from unittest import mock
 
-import numpy as np
 import PIL
 import torch
 import torchvision
@@ -36,17 +37,17 @@
     PYAV_AVAILABLE or VIDEO_READER_AVAILABLE, "No video backend available"
 )
 class TestVideoDataset(unittest.TestCase):
-    def tearDown(self):
+    def tearDown(self) -> None:
         # Make sure to set the default backend to not interfere with other tests.
         torchvision.set_video_backend(DEFAULT_BACKEND)
 
-    def ensure_dir(self, path_to_folder: str):
+    def ensure_dir(self, path_to_folder: str) -> None:
         if not os.path.exists(path_to_folder):
             os.makedirs(path_to_folder)
 
     def create_dataset_specified_frames_per_video(
-        self, frames_per_video: List[int], w=32, h=32, c=3
-    ):
+        self, frames_per_video: list[int], w: int = 32, h: int = 32, c: int = 3
+    ) -> None:
         self.input_dir = tempfile.mkdtemp()
         self.ensure_dir(self.input_dir)
         self.frames_over_videos = [
@@ -58,9 +59,16 @@ def create_dataset_specified_frames_per_video(
         for frames in self.frames_over_videos:
             path = os.path.join(self.input_dir, f"output-{len(frames):03}.avi")
             print(path)
-            out = torchvision.io.write_video(path, self.frames_over_videos, frames)
-
-    def create_dataset(self, n_videos=5, n_frames_per_video=10, w=32, h=32, c=3):
+            out = torchvision.io.write_video(filename=path, video_array=frames, fps=1)
+
+    def create_dataset(
+        self,
+        n_videos: int = 5,
+        n_frames_per_video: int = 10,
+        w: int = 32,
+        h: int = 32,
+        c: int = 3,
+    ) -> None:
         self.n_videos = n_videos
         self.n_frames_per_video = n_frames_per_video
 
@@ -72,13 +80,15 @@ def create_dataset(self, n_videos=5, n_frames_per_video=10, w=32, h=32, c=3):
         for i in range(n_videos):
             path = os.path.join(self.input_dir, f"output-{i}.avi")
             print(path)
-            out = torchvision.io.write_video(path, self.frames, n_frames_per_video)
+            out = torchvision.io.write_video(
+                filename=path, video_array=self.frames, fps=1
+            )
 
     @unittest.skipUnless(
         PYAV_AVAILABLE and VIDEO_READER_AVAILABLE,
         "pyav and video_reader backends must be both available",
     )
-    def test_video_similar_timestamps_for_different_backends(self):
+    def test_video_similar_timestamps_for_different_backends(self) -> None:
         frames_per_video = list(range(1, 10))
         self.create_dataset_specified_frames_per_video(frames_per_video)
 
@@ -115,7 +125,7 @@ def test_video_similar_timestamps_for_different_backends(self):
 
         shutil.rmtree(self.input_dir)
 
-    def test_video_dataset_tqdm_args(self):
+    def test_video_dataset_tqdm_args(self) -> None:
         self.create_dataset()
         desc = "test_video_dataset_tqdm_args description asdf"
         f = io.StringIO()
@@ -131,7 +141,7 @@ def test_video_dataset_tqdm_args(self):
         printed = f.getvalue()
         self.assertTrue(desc in printed)
 
-    def test_video_dataset_init_dataloader(self):
+    def test_video_dataset_init_dataloader(self) -> None:
         self.create_dataset()
         dataset_4_workers = LightlyDataset(
             self.input_dir, num_workers_video_frame_counting=4
@@ -164,7 +174,7 @@ def test_video_dataset_from_folder__video_reader(self) -> None:
         torchvision.set_video_backend("video_reader")
         self._test_video_dataset_from_folder()
 
-    def _test_video_dataset_from_folder(self):
+    def _test_video_dataset_from_folder(self) -> None:
         self.create_dataset()
 
         # create dataset
@@ -190,7 +200,7 @@ def _test_video_dataset_from_folder(self):
 
         shutil.rmtree(self.input_dir)
 
-    def test_video_dataset_no_read_rights(self):
+    def test_video_dataset_no_read_rights(self) -> None:
         n_videos = 7
         self.create_dataset(n_videos=n_videos)
 
@@ -216,21 +226,27 @@ def test_video_dataset_no_read_rights(self):
                 dataset = LightlyDataset(self.input_dir)
 
     @unittest.skipUnless(PYAV_AVAILABLE, "PyAV unavailable")
-    def test_video_dataset_non_increasing_timestamps__pyav(self):
+    def test_video_dataset_non_increasing_timestamps__pyav(self) -> None:
         torchvision.set_video_backend("pyav")
         self._test_video_dataset_non_increasing_timestamps()
 
     @unittest.skipUnless(VIDEO_READER_AVAILABLE, "video_reader unavailable")
-    def test_video_dataset_non_increasing_timestamps__video_reader(self):
+    def test_video_dataset_non_increasing_timestamps__video_reader(self) -> None:
         torchvision.set_video_backend("video_reader")
         self._test_video_dataset_non_increasing_timestamps()
 
-    def _test_video_dataset_non_increasing_timestamps(self):
+    def _test_video_dataset_non_increasing_timestamps(self) -> None:
         self.create_dataset(n_videos=2, n_frames_per_video=5)
 
         # overwrite the _make_dataset function to return a wrong timestamp
-        def _make_dataset_with_non_increasing_timestamps(*args, **kwargs):
+        def _make_dataset_with_non_increasing_timestamps(
+            *args: tuple[
+                str, tuple[str] | None, bool | None, str, dict[str, Any] | None, int
+            ],
+            **kwargs: dict[str, Any],
+        ) -> tuple[list[str], list[int], list[int], list[int]]:
             video_instances, timestamps, offsets, fpss = _make_dataset(*args, **kwargs)
+            print(video_instances, timestamps, offsets, fpss)
             # set timestamp of 4th frame in 1st video to timestamp of 2nd frame.
             timestamps[0][3] = timestamps[0][1]
             return video_instances, timestamps, offsets, fpss
@@ -272,16 +288,16 @@ def _make_dataset_with_non_increasing_timestamps(*args, **kwargs):
             self.assertEqual(total_frames, len(dataset))
 
     @unittest.skipUnless(PYAV_AVAILABLE, "PyAV unavailable")
-    def test_video_dataset_dataloader__pyav(self):
+    def test_video_dataset_dataloader__pyav(self) -> None:
         torchvision.set_video_backend("pyav")
         self._test_video_dataset_dataloader()
 
     @unittest.skipUnless(VIDEO_READER_AVAILABLE, "video_reader unavailable")
-    def test_video_dataset_dataloader__video_reader(self):
+    def test_video_dataset_dataloader__video_reader(self) -> None:
         torchvision.set_video_backend("video_reader")
         self._test_video_dataset_dataloader()
 
-    def _test_video_dataset_dataloader(self):
+    def _test_video_dataset_dataloader(self) -> None:
         self.create_dataset()
         dataset = VideoDataset(self.input_dir, extensions=self.extensions)
         dataloader = torch.utils.data.DataLoader(
@@ -294,7 +310,7 @@ def _test_video_dataset_dataloader(self):
         for batch in dataloader:
             pass
 
-    def test_find_non_increasing_timestamps(self):
+    def test_find_non_increasing_timestamps(self) -> None:
         # no timestamps
         non_increasing = _find_non_increasing_timestamps([])
         self.assertListEqual(non_increasing, [])