From 6351e3db135be2b68721f85ed4d76ca944a96dd2 Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 11:49:05 +0100 Subject: [PATCH 01/10] Added model tests (WIP --- .../test_image_model_training.py | 89 ++++++++++++++++ .../test_video_model_training.py | 95 ++++++++++++++++++ tests/model_training_data.zip | Bin 0 -> 3092230 bytes 3 files changed, 184 insertions(+) create mode 100644 tests/model_training/test_image_model_training.py create mode 100644 tests/model_training/test_video_model_training.py create mode 100644 tests/model_training_data.zip diff --git a/tests/model_training/test_image_model_training.py b/tests/model_training/test_image_model_training.py new file mode 100644 index 000000000..f0c38ff66 --- /dev/null +++ b/tests/model_training/test_image_model_training.py @@ -0,0 +1,89 @@ +import tempfile +from pathlib import Path +from zipfile import ZipFile + +from darwin.dataset.split_manager import split_dataset +from darwin.torch.dataset import ( + ClassificationDataset, + InstanceSegmentationDataset, + ObjectDetectionDataset, +) + + +class TestImageDatasetLoading: + def run_split_and_load_image_dataset_test( + self, dataset_name, dataset_class, expected_splits, split_values + ): + with tempfile.TemporaryDirectory() as tmpdir: + with ZipFile("tests/model_training_data.zip") as zfile: + zfile.extractall(tmpdir) + dataset_path = Path(tmpdir) / "model_training_data" / dataset_name + + split_dataset( + dataset_path=dataset_path, + release_name="complete", + val_percentage=0.1, + test_percentage=0.2, + ) + + split_types = ["random", "stratified"] + partitions = ["test", "train", "val"] + for split_type in split_types: + for partition in partitions: + dataset_partition = dataset_class( + dataset_path=dataset_path, + release_name="complete", + partition=partition, + split_type=split_type, + split=split_values, + ) + assert ( + len(dataset_partition.annotations_path) + == expected_splits[f"{split_type}_{partition}"] + ) + assert ( + len(dataset_partition.images_path) + == expected_splits[f"{split_type}_{partition}"] + ) + + def test_split_and_load_classification_dataset_images(self): + expected_splits = { + "random_test": 40, + "random_train": 140, + "random_val": 20, + "stratified_test": 40, + "stratified_train": 140, + "stratified_val": 20, + } + self.run_split_and_load_image_dataset_test( + "classification-test", ClassificationDataset, expected_splits, "140_20_40" + ) + + def test_split_and_load_instance_segmentation_dataset_images(self): + expected_splits = { + "random_test": 3, + "random_train": 7, + "random_val": 2, + "stratified_test": 3, + "stratified_train": 7, + "stratified_val": 2, + } + self.run_split_and_load_image_dataset_test( + "instance-segmentation-test", + InstanceSegmentationDataset, + expected_splits, + "7_2_3", + ) + + def test_split_and_load_object_detection_dataset_images(self): + expected_splits = { + "random_test": 11, + "random_train": 37, + "random_val": 6, + "stratified_test": 11, + "stratified_train": 37, + "stratified_val": 6, + } + self.run_split_and_load_image_dataset_test( + "object-detection-test", ObjectDetectionDataset, expected_splits, "37_6_11" + ) diff --git a/tests/model_training/test_video_model_training.py b/tests/model_training/test_video_model_training.py new file mode 100644 index 000000000..6f1a92e02 --- /dev/null +++ b/tests/model_training/test_video_model_training.py @@ -0,0 +1,95 @@ +import tempfile +from pathlib import Path +from zipfile import ZipFile + +from darwin.dataset.split_manager import split_dataset +from darwin.torch.dataset import ( + ClassificationDataset, + InstanceSegmentationDataset, + ObjectDetectionDataset, +) + + +class TestVideoDatasetLoading: + def run_split_and_load_video_dataset_test( + self, dataset_name, dataset_class, expected_splits, split_values + ): + with tempfile.TemporaryDirectory() as tmpdir: + with ZipFile("tests/model_training_data.zip") as zfile: + zfile.extractall(tmpdir) + dataset_path = Path(tmpdir) / "model_training_data" / dataset_name + + split_dataset( + dataset_path=dataset_path, + release_name="complete", + val_percentage=0.1, + test_percentage=0.2, + ) + + split_types = ["random", "stratified"] + partitions = ["test", "train", "val"] + for split_type in split_types: + for partition in partitions: + dataset_partition = dataset_class( + dataset_path=dataset_path, + release_name="complete", + partition=partition, + split_type=split_type, + split=split_values, + ) + assert ( + len(dataset_partition.annotations_path) + == expected_splits[f"{split_type}_{partition}"] + ) + assert ( + len(dataset_partition.images_path) + == expected_splits[f"{split_type}_{partition}"] + ) + + def test_split_and_load_classification_dataset_video(self): + expected_splits = { + "random_test": 60, + "random_train": 210, + "random_val": 30, + "stratified_test": 60, + "stratified_train": 210, + "stratified_val": 30, + } + self.run_split_and_load_video_dataset_test( + "classification-test-video", + ClassificationDataset, + expected_splits, + "210_30_60", + ) + + def test_split_and_load_instance_segmentation_dataset_video(self): + expected_splits = { + "random_test": 30, + "random_train": 105, + "random_val": 15, + "stratified_test": 30, + "stratified_train": 105, + "stratified_val": 15, + } + self.run_split_and_load_video_dataset_test( + "instance-segmentation-test-video", + InstanceSegmentationDataset, + expected_splits, + "105_15_30", + ) + + def test_split_and_load_object_detection_dataset_video(self): + expected_splits = { + "random_test": 30, + "random_train": 105, + "random_val": 15, + "stratified_test": 30, + "stratified_train": 105, + "stratified_val": 15, + } + self.run_split_and_load_video_dataset_test( + "object-detection-test-video", + ObjectDetectionDataset, + expected_splits, + "105_15_30", + ) diff --git a/tests/model_training_data.zip b/tests/model_training_data.zip new file mode 100644 index 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zwOA#(GvcqgjeHJ4{cPyUU-sx*d+%WS=W2-Ry2p%eXhyDM)q}T zPNzFC`&haxY+PX%O|V?qpukuTnz%c#j( z@W};-bV@eYlMCi?M&A=a^gQFLgeRMyXk3q^Re3xDM!&5q0~(jCr<^XpfX1b2O4k+R;OTL4Cp{V& zs!Q81xDAhV?W^=?WTs9Wy1*MoPkJi@8W*YYeO5Ta)8lc`YUC#uWTIM`buxp|&Fa#l zk%8Lk>%hA(I?h!FG%im&9~;;cp3}M1GN5sB8g`*^9(bg^BI(h{H2s|R_V|9G^6m=1 zlEwap@4gs9w9=ZZO^Y;_$V3fxy%`CQwI)&qHL_6`-!1qERzHuCLye2nJBJ+;;2F|qrwnRjrB*F6tO2aP zdPN2`GE zKL^~8OmZbuJ8*?+^yBl(W`pRDzA~V3o!Z6AwlX}@jU#11<1%&NuslOx^rRSiG_q0y z+vPa~qtES-0gam;ZM)bmh0&$2(4&!!I-~EzFEF~#8yV2JM9ouba4L*mQ=}%{>E-8= zhb+_@gD!cLDKOf2i4165oIanjEEkM+-!20hw~2ak=DhAOdf6peVe7e?3qR|YhYrrAI%dfsjbqbC-sO@4BL z(li_B$yF@N!03lH>CsS{W&{0VfBwfX+PRqwXdq3qfqs{szXyz7>LmjjNYiYfFTJd< jfYF~v(4(O=1<|?l2yZ@9q~%G=vv97F!hKO~;lKU|uqEvI literal 0 HcmV?d00001 From 702d8f37e9367cd84571768ff5736432e1e1b0bb Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 11:59:52 +0100 Subject: [PATCH 02/10] Fixed path for video frames pulled with folders --- darwin/dataset/download_manager.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/darwin/dataset/download_manager.py b/darwin/dataset/download_manager.py index f0138ba33..9b7ef204d 100644 --- a/darwin/dataset/download_manager.py +++ b/darwin/dataset/download_manager.py @@ -223,6 +223,7 @@ def _download_image_from_json_annotation( parent_path, annotation_path, video_frames, + use_folders, ) if force_slots: return _download_all_slots_from_json_annotation( @@ -235,6 +236,7 @@ def _download_image_from_json_annotation( parent_path, annotation_path, video_frames, + use_folders, ) return [] @@ -302,12 +304,15 @@ def _download_single_slot_from_json_annotation( parent_path: Path, annotation_path: Path, video_frames: bool, + use_folders: bool = True, ) -> Iterable[Callable[[], None]]: slot = annotation.slots[0] generator = [] if video_frames and slot.type != "image": - video_path: Path = parent_path / annotation_path.stem + video_path: Path = parent_path / ( + annotation_path.stem if not use_folders else Path(annotation.filename).stem + ) video_path.mkdir(exist_ok=True, parents=True) # Indicates it's a long video and uses the segment and manifest From b7527db1da1169cfbf885b0e4c18992d4645ad8b Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 12:26:34 +0100 Subject: [PATCH 03/10] Added model training data & tests --- darwin/dataset/download_manager.py | 2 +- tests/data.zip | Bin 293128 -> 293573 bytes tests/model_training_data.zip | Bin 3092230 -> 3967557 bytes 3 files changed, 1 insertion(+), 1 deletion(-) diff --git a/darwin/dataset/download_manager.py b/darwin/dataset/download_manager.py index 9b7ef204d..816966231 100644 --- a/darwin/dataset/download_manager.py +++ b/darwin/dataset/download_manager.py @@ -344,7 +344,7 @@ def _download_single_slot_from_json_annotation( image_url = image["url"] image_filename = image["file_name"] suffix = Path(image_filename).suffix - stem = annotation_path.stem + stem = Path(annotation.filename).stem filename = str(Path(stem + suffix)) 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z@97Xww(-!BZEzKxiiMP+0R94|sbp@`I#ONO-I_yQp5^Jk^wEiilGAqZW0;DnWeli} zoT?++u;p_K5?hv-TlxWO*^`w5k89`@JX*>5qv0lQC33$mAe3~ipl-!`I9U1nDkFU^ z$pxYdn}gkoF&AxK>qOg-m4jjFn!*M0_wD1L4=^W8j$73rHd*x}NY+DmGE>3Qp=di2 z&MtgCIF)MV08gjVC3FfDWn(X0s7UUN0ok+`HQ3#k*iq^?fDVoV*^hnnlqpGyg5?wn zS?XZeXh4IeiYTu8P@w2w)P#~_nS}t7|_nzC!#J!@`glh#E%8E z+*Q#AE&x%pv0%V2pV5XH`xkP9{ZVKk`e+!=D8 zsgoV!VNT@LWF#u%S`anmfQC&PGb0U2R*eE9xEw?ccd0U_KQj{BTW3UdTAZ5*9!^dX zJm9(zHPP1@$r()48eW-Bt3%JYHbjkoGAG%D@txtlz&ak+hbVa3jpviWNiw`J63H3z zEXM6FY1`Ol8`u&45xj(rvhk;($GAMCK(*i*VElm7(y<>|fJswJH@c0$??y9))0cu@ z5x|1QRG1pcZk(DoRhU2mb%au%n;{iN{&`eYzwhA`PT>(gJ64if(_tg((u=cSd(@X$ zTDtpmP~1J4=fwpfic%<*ODVfVPT^V*1%-K?2Hu{=^2Y4pd1E&VJ0;O$!x2y68jpHB zdkIsfvM<}Hd9>vlT;#f*P}kCfH%k4V_*pr3Oh`D;~Jr$*Bn z-~S#-HiozWL{Sng+<7+4jNoPhnKVxxKrH_48?&xVc~z9a;~Ef!GV+&S_!ndRr%45# lVW}`(0iwqj2HV+}C<$N5E%v Date: Wed, 19 Jun 2024 12:43:53 +0100 Subject: [PATCH 04/10] Added get_annotations() test (WIP) --- tests/darwin/dataset/dataset_utils_test.py | 83 ++++++++++++++++------ 1 file changed, 60 insertions(+), 23 deletions(-) diff --git a/tests/darwin/dataset/dataset_utils_test.py b/tests/darwin/dataset/dataset_utils_test.py index cee354aec..13420a43e 100644 --- a/tests/darwin/dataset/dataset_utils_test.py +++ b/tests/darwin/dataset/dataset_utils_test.py @@ -1,15 +1,19 @@ import shutil +import tempfile from pathlib import Path from typing import Dict from unittest.mock import MagicMock, patch +from zipfile import ZipFile import orjson as json import pytest +from darwin.dataset.split_manager import split_dataset from darwin.dataset.utils import ( compute_distributions, exhaust_generator, extract_classes, + get_annotations, get_external_file_type, get_release_path, parse_external_file_path, @@ -457,40 +461,73 @@ def test_parse_external_file_paths(self): ) -''' class TestGetAnnotations: def test_basic_functionality( self, - team_extracted_dataset_path, - team_dataset_release_path, - annotations_path, - split_path ): """ Basic functionality test for the `get_annotations` function. """ - - # Test with basic setup - annotations = list(get_annotations(dataset_path=team_extracted_dataset_path)) - assert len(annotations) > 0, "Expected to find some annotations" - - # Add more assertions here to validate the structure of the returned annotations + with tempfile.TemporaryDirectory() as tmpdir: + with ZipFile("tests/model_training_data.zip") as zfile: + zfile.extractall(tmpdir) + dataset_path = ( + Path(tmpdir) / "model_training_data" / "classification-test" + ) + annotations = list( + get_annotations( + dataset_path=dataset_path, + release_name="complete", + annotation_type="tag", + annotation_format="darwin", + ) + ) + assert len(annotations) == 200 + assert annotations[0]["annotations"][0]["tag"] == {} def test_partition_handling( self, - team_extracted_dataset_path, - team_dataset_release_path, - annotations_path, - split_path ): """ Test the partition handling of the `get_annotations` function. """ - - # Assuming there's a train partition in the test dataset - annotations = list(get_annotations(dataset_path=team_extracted_dataset_path, partition="train")) - assert len(annotations) > 0, "Expected to find some annotations for the train partition" - - # Add more assertions here to validate the structure of the returned annotations - # Repeat for other partitions (e.g., val, test) if present in the mock data -''' + with tempfile.TemporaryDirectory() as tmpdir: + with ZipFile("tests/model_training_data.zip") as zfile: + zfile.extractall(tmpdir) + dataset_path = ( + Path(tmpdir) / "model_training_data" / "classification-test" + ) + split_dataset( + dataset_path=dataset_path, + release_name="complete", + val_percentage=0.1, + test_percentage=0.2, + ) + split_types = ["random", "stratified"] + partitions = ["test", "train", "val"] + expected_splits = { + "random_test": 40, + "random_train": 140, + "random_val": 20, + "stratified_test": 40, + "stratified_train": 140, + "stratified_val": 20, + } + for split_type in split_types: + for partition in partitions: + annotations = list( + get_annotations( + dataset_path=dataset_path, + release_name="complete", + annotation_type="tag", + annotation_format="darwin", + partition=partition, + split_type=split_type, + split="140_20_40", + ) + ) + assert ( + len(annotations) + == expected_splits[f"{split_type}_{partition}"] + ) + assert annotations[0]["annotations"][0]["tag"] == {} From a101d1cfe719ab5d95f0de519bb7fb2e795572f1 Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 12:55:47 +0100 Subject: [PATCH 05/10] Fixed type issue for get_annotations() --- darwin/dataset/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/darwin/dataset/utils.py b/darwin/dataset/utils.py index 54ed3231f..f56a0beba 100644 --- a/darwin/dataset/utils.py +++ b/darwin/dataset/utils.py @@ -654,7 +654,7 @@ def _load_and_format_annotations( ) elif annotation_format == "darwin": for annotation_path in annotations_paths: - record = attempt_decode(annotation_path) + record = attempt_decode(Path(annotation_path)) yield record From 8945d69621987922cb265d6c4a28fb7a07df7afd Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 12:56:57 +0100 Subject: [PATCH 06/10] Re-added convert_xyxy_to_bounding_box() --- darwin/utils/utils.py | 29 +++++++++++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/darwin/utils/utils.py b/darwin/utils/utils.py index f2549ffa6..df77ce93b 100644 --- a/darwin/utils/utils.py +++ b/darwin/utils/utils.py @@ -1300,6 +1300,35 @@ def convert_polygons_to_sequences( return sequences +def convert_xyxy_to_bounding_box(box: List[Union[int, float]]) -> dt.BoundingBox: + """ + Converts a list of xy coordinates representing a bounding box into a dictionary. + This is used by in-platform model training. + + Parameters + ---------- + box : List[Union[int, float]] + List of arrays of coordinates in the format [x1, y1, x2, y2] + + Returns + ------- + BoundingBox + Bounding box in the format ``{x: x1, y: y1, h: height, w: width}``. + + Raises + ------ + ValueError + If ``box`` has an incorrect format. + """ + if not isinstance(box[0], float) and not isinstance(box[0], int): + raise ValueError("Unknown input format") + + x1, y1, x2, y2 = box + width = x2 - x1 + height = y2 - y1 + return {"x": x1, "y": y1, "w": width, "h": height} + + def convert_polygons_to_mask( polygons: List, height: int, width: int, value: Optional[int] = 1 ) -> np.ndarray: From c7baaa16eb6eecef540db10dd2548aa6b090ca59 Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 13:14:48 +0100 Subject: [PATCH 07/10] get_annotations() fixes --- darwin/dataset/utils.py | 92 +++++++++++++++++++++-------------------- 1 file changed, 47 insertions(+), 45 deletions(-) diff --git a/darwin/dataset/utils.py b/darwin/dataset/utils.py index f56a0beba..e948c11b2 100644 --- a/darwin/dataset/utils.py +++ b/darwin/dataset/utils.py @@ -400,11 +400,11 @@ def create_bbox_object(obj, box_mode, classes=None): def get_annotations( dataset_path: PathLike, partition: Optional[str] = None, + split_type: Optional[str] = "random", + annotation_format: str = "coco", split: Optional[str] = "default", - split_type: Optional[str] = None, annotation_type: str = "polygon", release_name: Optional[str] = None, - annotation_format: str = "coco", ignore_inconsistent_examples: bool = False, ) -> Iterator[Dict[str, Any]]: """ @@ -415,17 +415,17 @@ def get_annotations( dataset_path : PathLike Path to the location of the dataset on the file system. partition : Optional[str], default: None - Selects one of the partitions ``[train, val, test]``. + Selects one of the partitions ``[train, val, test, None]``. If not specified, all annotations are returned. + split_type : Optional[str], default: "random" + Heuristic used to do the split ``[random, stratified]``. If not specified, random is used. + annotation_format : str + Re-formatting of the annotation when loaded ``[coco, darwin]``.. split : Optional[str], default: "default" Selects the split that defines the percentages used (use 'default' to select the default split). - split_type : Optional[str], default: None - Heuristic used to do the split ``[random, stratified, None]``. annotation_type : str, default: "polygon" The type of annotation classes ``[tag, bounding_box, polygon]``. release_name : Optional[str], default: None Version of the dataset. - annotation_format : Optional[str], default: "coco" - Re-formatting of the annotation when loaded ``[coco, darwin]``. ignore_inconsistent_examples : bool, default: False Ignore examples for which we have annotations, but either images are missing, or more than one images exist for the same annotation. @@ -467,18 +467,18 @@ def get_annotations( ) if partition: - stems = _get_stems_from_split( - release_path, split, split_type, annotation_type, partition + annotation_filepaths = _get_annotation_filepaths_from_split( + release_path, annotation_type, partition, split_type, split=split ) else: - stems = get_annotation_files_from_dir(annotations_dir) + annotation_filepaths = get_annotation_files_from_dir(annotations_dir) ( images_paths, annotations_paths, invalid_annotation_paths, ) = _map_annotations_to_images( - stems, annotations_dir, images_dir, ignore_inconsistent_examples + annotation_filepaths, images_dir, ignore_inconsistent_examples ) print(f"Found {len(invalid_annotation_paths)} invalid annotations") @@ -505,55 +505,57 @@ def _validate_inputs( Validates the input parameters for partition, split_type, and annotation_type. Args: - partition (str, None): Dataset partition. Should be 'train', 'val', 'test' or None. - split_type (str, None): Type of dataset split. Can be 'random', 'stratified' or None. + partition (str, None): Dataset partition. Should be 'train', 'val', 'test', or None. + split_type (str, None): Type of dataset split. Can be 'random' or 'stratified'. annotation_type (str): Type of annotations. Can be 'tag', 'polygon', or 'bounding_box'. Raises: ValueError: If the input parameters do not match the expected values. """ if partition not in ["train", "val", "test", None]: - raise ValueError("partition should be either 'train', 'val', 'test', or None") - if split_type not in ["random", "stratified", None]: - raise ValueError("split_type should be either 'random', 'stratified', or None") + raise ValueError("partition should be either 'train', 'val', 'test', or 'None'") + if split_type not in ["random", "stratified"]: + raise ValueError("split_type should be either 'random', or 'stratified'") if annotation_type not in ["tag", "polygon", "bounding_box"]: raise ValueError( "annotation_type should be either 'tag', 'bounding_box', or 'polygon'" ) -def _get_stems_from_split( +def _get_annotation_filepaths_from_split( release_path: Path, - split: str, - split_type: Union[str, None], annotation_type: str, - partition: Union[str, None], -) -> Generator: + partition: str, + split_type: str, + split: Optional[str] = "default", +) -> Generator[str, None, None]: """ - Determines the file stems based on the dataset split and other parameters. + Determines the filpaths based on the dataset split and other parameters. Args: - release_path (Path): Path to the dataset release. - split (str): Dataset split identifier. - split_type (str, None): Type of dataset split. Can be 'random', 'stratified' or None. - annotation_type (str): Type of annotations. Can be 'tag', 'polygon', or 'bounding_box'. - partition (str, None): Dataset partition. Should be 'train', 'val', 'test' or None. + release_path : Path + Path to the dataset release. + annotation_type : str + Type of annotations. Can be 'tag', 'polygon', or 'bounding_box'. + partition : str + Dataset partition. Should be 'train', 'val', 'test'. + split_type : str + Type of dataset split. Can be 'random' or 'stratified'. + split : Optional[str] + Dataset split identifier. Returns: - Generator[str]: File stems for the dataset. + Generator: [str, None, None] + Filepaths for the dataset. Raises: ValueError: If the split_type is invalid. FileNotFoundError: If the dataset partition file is not found. """ - if split_type is None: - split_file = f"{partition}.txt" - elif split_type == "random": + if split_type == "random": split_file = f"{split_type}_{partition}.txt" elif split_type == "stratified": split_file = f"{split_type}_{annotation_type}_{partition}.txt" - else: - raise ValueError(f"Invalid split_type ({split_type})") split_path: Path = release_path / "lists" / str(split) / split_file @@ -567,8 +569,7 @@ def _get_stems_from_split( def _map_annotations_to_images( - stems: List[str], - annotations_dir: Path, + annotation_filepaths: Generator[str, None, None], images_dir: Path, ignore_inconsistent_examples: bool, ) -> Tuple[List[Path], List[Path], List[Path]]: @@ -576,7 +577,7 @@ def _map_annotations_to_images( Maps annotations to their corresponding images based on the file stems. Args: - stems (List[str]): List of file stems. + annotation_filepaths (Generator[str, None, None]): List of annotation filepaths. annotations_dir (Path): Directory containing annotation files. images_dir (Path): Directory containing image files. ignore_inconsistent_examples (bool): Flag to determine if inconsistent examples should be ignored. @@ -591,14 +592,14 @@ def _map_annotations_to_images( annotations_paths = [] invalid_annotation_paths = [] with_folders = any(item.is_dir() for item in images_dir.iterdir()) - for annotation_path in get_annotation_files_from_dir(annotations_dir): + for annotation_path in annotation_filepaths: darwin_json = stream_darwin_json(Path(annotation_path)) image_path = get_image_path_from_stream( darwin_json, images_dir, Path(annotation_path), with_folders ) if image_path.exists(): images_paths.append(image_path) - annotations_paths.append(annotation_path) + annotations_paths.append(Path(annotation_path)) continue else: if ignore_inconsistent_examples: @@ -618,7 +619,7 @@ def _load_and_format_annotations( annotation_format: str, annotation_type: str, classes: List[str], -) -> Generator: +) -> Generator[str, None, None]: """ Loads and formats annotations based on the specified format and type. @@ -795,16 +796,17 @@ def compute_distributions( ) if not split_file.exists(): split_file = split_path / f"random_{partition}.txt" - stems: List[str] = [e.rstrip("\n\r") for e in split_file.open()] - for stem in stems: - if not stem.endswith(".json"): - stem = f"{stem}.json" - annotation_path: Path = annotations_dir / stem + annotation_filepaths: List[str] = [ + e.rstrip("\n\r") for e in split_file.open() + ] + for annotation_filepath in annotation_filepaths: + if not annotation_filepath.endswith(".json"): + annotation_filepath = f"{annotation_filepath}.json" + annotation_path: Path = annotations_dir / annotation_filepath annotation_file: Optional[dt.AnnotationFile] = parse_path( annotation_path ) - if annotation_file is None: continue From e7ab90a6135cae5fcb84b1eb522a68162ffe1a25 Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 13:17:43 +0100 Subject: [PATCH 08/10] Finalised test data --- tests/model_training_data.zip | Bin 3967557 -> 3964354 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/tests/model_training_data.zip b/tests/model_training_data.zip index 79b887a1bdabb3b6f2a14990c31d59a4c9141d36..8c3d38acfe85486171433aa7c76e43f8ec7c4a15 100644 GIT binary patch delta 140627 zcma%E2YeO9)+asObaHPXKnk4%LK0diN`msJ0zpJk2!w8^DM*I|1w@JjqZvBEf&v0T zgb^tTMHFeF2ucm8Akq?06cG5%p4q#*vpc)_c)z^&e)s(6^qD!kQ}(+L@44)IT<+qV z+|AA1UP<~FIC8OXBU`N_nZs+tU#%mH+t&!HGV)YkB*K5WSF2PhEN`Y;)$Ar6dJpV9 zeq83TKCk#y@~R7H=ighCd@8xP|Lp>3iRo?9zQ_K!!2f+;t8>TEZ~t6;tZM3s8ndED z|NOwUUYDrOJ^Dv|cC+wTd(F>ZD{ZsjWvEFEjZ=dnUJRV& zcAzLb!gs~KF@^i4xqrWMg?r0%8{KQm2&%cidXH4M&(muxAo=^Qym;l9t%3ccV$UA` zJUaY#*|=7=uKzvFzW?{bfq}CU7tGt*rRCb=ZtVk#&Q>3LYLWZ7r-8+N7xXQ13><&Z 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z@LBPr3jTs_3Bh6o8*r;7=$$P~X+|U3u@6Z5vDqX=8U;xO+bO8mH3~g6b=83BONuL_JfncfG@7`qe z{xGXjwo#yHec&CicK*%~r5a736?Je$dgt2likSa&JRG+ynhY)B&lBcWlx8#$^LasR z=UPosoY92JJpj}-m!>GsC@7i}|CA$yePip0^(>mT^Y!=>AFN%Vdg~owPgYnftY`iR M4QcGK!(p8N0+=?0YXATM From 855a5184bbf983c8680ba130679dafd1a7d3c4cc Mon Sep 17 00:00:00 2001 From: John Wilkie Date: Wed, 19 Jun 2024 20:44:58 +0100 Subject: [PATCH 09/10] Fixes for splitting video annotations --- darwin/dataset/remote_dataset.py | 14 ++++++++ darwin/utils/utils.py | 9 +++-- tests/darwin/dataset/remote_dataset_test.py | 12 +++---- .../utils/get_image_path_from_stream_test.py | 32 +++++++++++++++--- tests/model_training_data.zip | Bin 3964354 -> 3959616 bytes 5 files changed, 54 insertions(+), 13 deletions(-) diff --git a/darwin/dataset/remote_dataset.py b/darwin/dataset/remote_dataset.py index 68d2e1805..bbfe91ba7 100644 --- a/darwin/dataset/remote_dataset.py +++ b/darwin/dataset/remote_dataset.py @@ -163,6 +163,20 @@ def split_video_annotations(self, release_name: str = "latest") -> None: for frame_annotation in frame_annotations: annotation = self._build_image_annotation(frame_annotation, self.team) + # When splitting into frames, we need to read each frame individually + # Because we use the source name suffix, we need to adjust this to .png here + current_stem = Path( + annotation["item"]["slots"][0]["source_files"][0]["file_name"] + ).stem + annotation["item"]["slots"][0]["source_files"][0]["file_name"] = ( + current_stem + ".png" + ) + # We also need to account for the folder that this function creates + item_name = annotation["item"]["name"].split("/")[0] + if annotation["item"]["path"] == "/": + annotation["item"]["path"] += item_name + else: + annotation["item"]["path"] = item_name video_frame_annotations_path = annotations_path / annotation_file.stem video_frame_annotations_path.mkdir(exist_ok=True, parents=True) diff --git a/darwin/utils/utils.py b/darwin/utils/utils.py index df77ce93b..f6159de74 100644 --- a/darwin/utils/utils.py +++ b/darwin/utils/utils.py @@ -456,13 +456,18 @@ def get_image_path_from_stream( Path to the image file. """ try: + item_name_stem = Path(darwin_json["item"]["name"]).stem + source_name_suffix = Path( + darwin_json["item"]["slots"][0]["source_files"][0]["file_name"] + ).suffix + local_file_name = Path(item_name_stem + source_name_suffix) if not with_folders: - return images_dir / Path(darwin_json["item"]["name"]) + return images_dir / local_file_name else: return ( images_dir / (Path(darwin_json["item"]["path"].lstrip("/\\"))) - / Path(darwin_json["item"]["name"]) + / local_file_name ) except OSError: # Load in the JSON as normal diff --git a/tests/darwin/dataset/remote_dataset_test.py b/tests/darwin/dataset/remote_dataset_test.py index 584b5fd9a..d94b7209d 100644 --- a/tests/darwin/dataset/remote_dataset_test.py +++ b/tests/darwin/dataset/remote_dataset_test.py @@ -381,7 +381,7 @@ def test_works_on_videos( "schema_ref": "https://darwin-public.s3.eu-west-1.amazonaws.com/darwin_json/2.0/schema.json", "item": { "name": "test_video/0000000.png", - "path": "/", + "path": "/test_video", "source_info": { "dataset": { "name": "v7-darwin-json-v2", @@ -402,7 +402,7 @@ def test_works_on_videos( "height": 1080, "thumbnail_url": "", "source_files": [ - {"file_name": "test_video.mp4", "url": ""} + {"file_name": "test_video.png", "url": ""} ], } ], @@ -427,7 +427,7 @@ def test_works_on_videos( "schema_ref": "https://darwin-public.s3.eu-west-1.amazonaws.com/darwin_json/2.0/schema.json", "item": { "name": "test_video/0000001.png", - "path": "/", + "path": "/test_video", "source_info": { "dataset": { "name": "v7-darwin-json-v2", @@ -448,7 +448,7 @@ def test_works_on_videos( "height": 1080, "thumbnail_url": "", "source_files": [ - {"file_name": "test_video.mp4", "url": ""} + {"file_name": "test_video.png", "url": ""} ], } ], @@ -462,7 +462,7 @@ def test_works_on_videos( "schema_ref": "https://darwin-public.s3.eu-west-1.amazonaws.com/darwin_json/2.0/schema.json", "item": { "name": "test_video/0000002.png", - "path": "/", + "path": "/test_video", "source_info": { "dataset": { "name": "v7-darwin-json-v2", @@ -483,7 +483,7 @@ def test_works_on_videos( "height": 1080, "thumbnail_url": "", "source_files": [ - {"file_name": "test_video.mp4", "url": ""} + {"file_name": "test_video.png", "url": ""} ], } ], diff --git a/tests/darwin/utils/get_image_path_from_stream_test.py b/tests/darwin/utils/get_image_path_from_stream_test.py index fb4abc615..e4da62851 100644 --- a/tests/darwin/utils/get_image_path_from_stream_test.py +++ b/tests/darwin/utils/get_image_path_from_stream_test.py @@ -5,20 +5,42 @@ class TestGetImagePathFromStream: def test_with_folders_true(self): - darwin_json = {"item": {"name": "image.jpg", "path": "/folder"}} - images_dir = Path("/images") + darwin_json = { + "item": { + "name": "item_name", + "path": "/folder", + "slots": [ + { + "slot_name": "0", + "source_files": [{"file_name": "source_name.jpg"}], + } + ], + } + } annotation_filepath = Path("/annotations/annotation.json") - expected = Path("/images/folder/image.jpg") + images_dir = Path("/images") + expected = Path("/images/folder/item_name.jpg") result = get_image_path_from_stream( darwin_json, images_dir, annotation_filepath, True ) assert result == expected def test_with_folders_false(self): - darwin_json = {"item": {"name": "image.jpg", "path": "/folder"}} + darwin_json = { + "item": { + "name": "item_name", + "path": "/folder", + "slots": [ + { + "slot_name": "0", + "source_files": [{"file_name": "source_name.jpg"}], + } + ], + } + } images_dir = Path("/images") annotation_filepath = Path("/annotations/annotation.json") - expected = Path("/images/image.jpg") + expected = Path("/images/item_name.jpg") result = get_image_path_from_stream( darwin_json, images_dir, annotation_filepath, False ) diff --git a/tests/model_training_data.zip b/tests/model_training_data.zip index 8c3d38acfe85486171433aa7c76e43f8ec7c4a15..928eb92c23eec39675e651c8c2f0fa10872e5a2d 100644 GIT binary patch delta 1374330 zcmeEv2~Zb+u1k&_1;?F_h0M1w|Z}_`jWA6eU5DRF=lZ<<}O^q?8C?S!q=w{B7V2q$mxcm 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insertion(+), 1 deletion(-) diff --git a/darwin/dataset/remote_dataset.py b/darwin/dataset/remote_dataset.py index bbfe91ba7..da517ae43 100644 --- a/darwin/dataset/remote_dataset.py +++ b/darwin/dataset/remote_dataset.py @@ -176,7 +176,7 @@ def split_video_annotations(self, release_name: str = "latest") -> None: if annotation["item"]["path"] == "/": annotation["item"]["path"] += item_name else: - annotation["item"]["path"] = item_name + annotation["item"]["path"] += "/" + item_name video_frame_annotations_path = annotations_path / annotation_file.stem video_frame_annotations_path.mkdir(exist_ok=True, parents=True) diff --git a/tests/model_training_data.zip b/tests/model_training_data.zip index 928eb92c23eec39675e651c8c2f0fa10872e5a2d..d50f6d20020095e08776c5c5699414944a92620b 100644 GIT binary patch delta 145108 zcmeEvcT`kI*mpn>SUS6l6F5H97A&-}}$&IrztYe)II1dG5^I+2RY2?2i5L z$j&XIdpQTgJHo$<`HS5e=xC>u5#rzC4prxN3mot=nx75ggoG(WS3eS6(R3j^`-vHZ-r_FZ&KHRyf$ng7`L&}C>IpUBUQDc3=_ 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