232 lines
7.8 KiB
Python
232 lines
7.8 KiB
Python
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# Copyright (C) CVAT.ai Corporation
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#
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# SPDX-License-Identifier: MIT
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import io
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from logging import Logger
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from pathlib import Path
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import cvat_sdk.datasets as cvatds
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import PIL.Image
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import pytest
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from cvat_sdk import Client, models
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from cvat_sdk.core.proxies.annotations import AnnotationUpdateAction
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from cvat_sdk.core.proxies.tasks import ResourceType
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from shared.utils.helpers import generate_image_files
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from .util import restrict_api_requests
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@pytest.fixture(autouse=True)
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def _common_setup(
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tmp_path: Path,
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fxt_login: tuple[Client, str],
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fxt_logger: tuple[Logger, io.StringIO],
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restore_redis_ondisk_per_function,
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restore_redis_inmem_per_function,
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):
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logger = fxt_logger[0]
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client = fxt_login[0]
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client.logger = logger
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client.config.cache_dir = tmp_path / "cache"
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api_client = client.api_client
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for k in api_client.configuration.logger:
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api_client.configuration.logger[k] = logger
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class TestTaskDataset:
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@pytest.fixture(autouse=True)
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def setup(
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self,
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tmp_path: Path,
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fxt_login: tuple[Client, str],
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):
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self.client = fxt_login[0]
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self.images = generate_image_files(10)
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image_dir = tmp_path / "images"
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image_dir.mkdir()
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image_paths = []
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for image in self.images:
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image_path = image_dir / image.name
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image_path.write_bytes(image.getbuffer())
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image_paths.append(image_path)
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self.task = self.client.tasks.create_from_data(
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models.TaskWriteRequest(
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"Dataset layer test task",
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labels=[
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models.PatchedLabelRequest(name="person"),
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models.PatchedLabelRequest(name="car"),
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],
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),
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resource_type=ResourceType.LOCAL,
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resources=image_paths,
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data_params={"chunk_size": 3},
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)
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self.expected_labels = sorted(self.task.get_labels(), key=lambda l: l.id)
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self.task.update_annotations(
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models.PatchedLabeledDataRequest(
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tags=[
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models.LabeledImageRequest(frame=8, label_id=self.expected_labels[0].id),
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models.LabeledImageRequest(frame=8, label_id=self.expected_labels[1].id),
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],
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shapes=[
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models.LabeledShapeRequest(
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frame=6,
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label_id=self.expected_labels[1].id,
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type=models.ShapeType("rectangle"),
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points=[1.0, 2.0, 3.0, 4.0],
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),
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],
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),
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action=AnnotationUpdateAction.CREATE,
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)
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@pytest.mark.parametrize("media_download_policy", cvatds.MediaDownloadPolicy)
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def test_basic(self, media_download_policy: cvatds.MediaDownloadPolicy):
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dataset = cvatds.TaskDataset(
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self.client, self.task.id, media_download_policy=media_download_policy
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)
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# verify that the cache is not empty
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assert list(self.client.config.cache_dir.iterdir())
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for expected_label, actual_label in zip(
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self.expected_labels, sorted(dataset.labels, key=lambda l: l.id)
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):
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assert expected_label.id == actual_label.id
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assert expected_label.name == actual_label.name
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assert len(dataset.samples) == self.task.size
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for index, sample in enumerate(dataset.samples):
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assert sample.frame_index == index
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assert sample.frame_name == self.images[index].name
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actual_image = sample.media.load_image()
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expected_image = PIL.Image.open(self.images[index])
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assert actual_image == expected_image
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assert not dataset.samples[0].annotations.tags
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assert not dataset.samples[1].annotations.shapes
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assert {tag.label_id for tag in dataset.samples[8].annotations.tags} == {
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label.id for label in self.expected_labels
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}
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assert not dataset.samples[8].annotations.shapes
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assert not dataset.samples[6].annotations.tags
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assert len(dataset.samples[6].annotations.shapes) == 1
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assert dataset.samples[6].annotations.shapes[0].type.value == "rectangle"
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assert dataset.samples[6].annotations.shapes[0].points == [1.0, 2.0, 3.0, 4.0]
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@pytest.mark.parametrize("media_download_policy", cvatds.MediaDownloadPolicy)
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def test_deleted_frame(self, media_download_policy: cvatds.MediaDownloadPolicy):
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self.task.remove_frames_by_ids([1])
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dataset = cvatds.TaskDataset(
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self.client, self.task.id, media_download_policy=media_download_policy
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)
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assert len(dataset.samples) == self.task.size - 1
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# sample #0 is still frame #0
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assert dataset.samples[0].frame_index == 0
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assert dataset.samples[0].media.load_image() == PIL.Image.open(self.images[0])
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# sample #1 is now frame #2
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assert dataset.samples[1].frame_index == 2
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assert dataset.samples[1].media.load_image() == PIL.Image.open(self.images[2])
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# sample #5 is now frame #6
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assert dataset.samples[5].frame_index == 6
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assert dataset.samples[5].media.load_image() == PIL.Image.open(self.images[6])
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assert len(dataset.samples[5].annotations.shapes) == 1
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def test_offline(self, monkeypatch: pytest.MonkeyPatch):
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dataset = cvatds.TaskDataset(
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self.client,
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self.task.id,
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update_policy=cvatds.UpdatePolicy.IF_MISSING_OR_STALE,
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)
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fresh_samples = list(dataset.samples)
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restrict_api_requests(monkeypatch)
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dataset = cvatds.TaskDataset(
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self.client,
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self.task.id,
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update_policy=cvatds.UpdatePolicy.NEVER,
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)
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cached_samples = list(dataset.samples)
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for fresh_sample, cached_sample in zip(fresh_samples, cached_samples):
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assert fresh_sample.frame_index == cached_sample.frame_index
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assert fresh_sample.annotations == cached_sample.annotations
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assert fresh_sample.media.load_image() == cached_sample.media.load_image()
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def test_update(self, monkeypatch: pytest.MonkeyPatch):
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dataset = cvatds.TaskDataset(
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self.client,
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self.task.id,
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)
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# Recreating the dataset should only result in minimal requests.
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restrict_api_requests(
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monkeypatch, allow_paths={f"/api/tasks/{self.task.id}", "/api/labels"}
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)
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dataset = cvatds.TaskDataset(
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self.client,
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self.task.id,
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)
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assert dataset.samples[6].annotations.shapes[0].label_id == self.expected_labels[1].id
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# After an update, the annotations should be redownloaded.
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monkeypatch.undo()
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self.task.update_annotations(
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models.PatchedLabeledDataRequest(
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shapes=[
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models.LabeledShapeRequest(
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id=dataset.samples[6].annotations.shapes[0].id,
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frame=6,
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label_id=self.expected_labels[0].id,
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type=models.ShapeType("rectangle"),
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points=[1.0, 2.0, 3.0, 4.0],
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),
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]
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)
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)
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dataset = cvatds.TaskDataset(
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self.client,
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self.task.id,
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)
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assert dataset.samples[6].annotations.shapes[0].label_id == self.expected_labels[0].id
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def test_no_annotations(self):
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dataset = cvatds.TaskDataset(self.client, self.task.id, load_annotations=False)
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for index, sample in enumerate(dataset.samples):
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assert sample.frame_index == index
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assert sample.frame_name == self.images[index].name
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actual_image = sample.media.load_image()
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expected_image = PIL.Image.open(self.images[index])
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assert actual_image == expected_image
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assert sample.annotations is None
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