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fsl_105.py

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+import os
+from pathlib import Path, PureWindowsPath
+from typing import Dict, List, Tuple
+
+try:
+    import cv2
+except:
+    print("Install the `cv2` package to use.")
+import datasets
+import pandas as pd
+
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Licenses, Tasks
+
+_CITATION = """\
+@article{tupal4476867fsl105,
+  title={FSL105: The Video Filipino Sign Language Sign Database of Introductory 105 FSL Signs},
+  author={Tupal, Isaiah Jassen Lizaso and Melvin, Cabatuan K},
+  journal={Available at SSRN 4476867}
+}
+"""
+
+_DATASETNAME = "fsl_105"
+
+_DESCRIPTION = """\
+FSL-105 is a video dataset for 105 different Filipino Sign Language (FSL) signs.
+Each sign is categorized into one of 10 categories and is each represented by approximately 20 four-second video samples.
+Signs were performed by adult deaf FSL signers on a blank blue background and reviewed by an FSL expert.
+"""
+
+_HOMEPAGE = "https://data.mendeley.com/datasets/48y2y99mb9/2"
+
+_LICENSE = Licenses.CC_BY_4_0.value
+
+_LOCAL = False
+
+_URLS = {
+    "clips": "https://prod-dcd-datasets-public-files-eu-west-1.s3.eu-west-1.amazonaws.com/de95a3c3-02f4-4a3f-9a9e-ce2371160275",
+    "train": "https://prod-dcd-datasets-public-files-eu-west-1.s3.eu-west-1.amazonaws.com/09c71779-3a2a-4c98-8d9b-0ef74f54d92a",
+    "test": "https://prod-dcd-datasets-public-files-eu-west-1.s3.eu-west-1.amazonaws.com/39af8117-6b44-47b9-a551-0bdc40837295",
+}
+
+_LANGUAGES = ["psp"]
+
+_SUPPORTED_TASKS = [Tasks.VIDEO_TO_TEXT_RETRIEVAL, Tasks.VIDEO_CAPTIONING]
+
+_SOURCE_VERSION = "1.0.0"
+
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class FSL105Dataset(datasets.GeneratorBasedBuilder):
+    """
+    FSL-105 is a video dataset for 105 different Filipino Sign Language (FSL) signs.
+    Each sign is categorized into one of 10 categories and is each represented by approximately 20 four-second video samples.
+    Signs were performed by adult deaf FSL signers on a blank blue background and reviewed by an FSL expert.
+    """
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_source",
+            version=SOURCE_VERSION,
+            description=f"{_DATASETNAME} source schema",
+            schema="source",
+            subset_id=f"{_DATASETNAME}",
+        ),
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_seacrowd_vidtext",
+            version=SEACROWD_VERSION,
+            description=f"{_DATASETNAME} SEACrowd schema",
+            schema="seacrowd_vidtext",
+            subset_id=f"{_DATASETNAME}",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    category = [
+        "CALENDAR",
+        "COLOR",
+        "DAYS",
+        "DRINK",
+        "FAMILY",
+        "FOOD",
+        "GREETING",
+        "NUMBER",
+        "RELATIONSHIPS",
+        "SURVIVAL",
+    ]
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "video_path": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "labels": datasets.ClassLabel(names=self.category),
+                    "metadata": {
+                        "resolution": {
+                            "width": datasets.Value("int64"),
+                            "height": datasets.Value("int64"),
+                        },
+                        "duration": datasets.Value("float32"),
+                        "fps": datasets.Value("float32"),
+                    },
+                }
+            )
+
+        elif self.config.schema == "seacrowd_vidtext":
+            features = schemas.video_features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        """Returns SplitGenerators."""
+
+        clips = dl_manager.download_and_extract(_URLS["clips"])
+        train = dl_manager.download_and_extract(_URLS["train"])
+        test = dl_manager.download_and_extract(_URLS["test"])
+
+        train_df = pd.read_csv(train)
+        test_df = pd.read_csv(test)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": {
+                        "clips": clips,
+                        "data": train_df,
+                    },
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": {"clips": clips, "data": test_df},
+                    "split": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+
+        for key, example in filepath["data"].iterrows():
+            video = cv2.VideoCapture(os.path.join(filepath["clips"], PureWindowsPath(example["vid_path"]).as_posix()))
+            fps = video.get(cv2.CAP_PROP_FPS)
+            frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
+            duration = frame_count / fps
+            vid_width = video.get(cv2.CAP_PROP_FRAME_WIDTH)
+            vid_height = video.get(cv2.CAP_PROP_FRAME_HEIGHT)
+
+            if self.config.schema == "source":
+                yield key, {
+                    "id": str(key),
+                    "video_path": os.path.join(filepath["clips"], example["vid_path"]),
+                    "text": example["label"],
+                    "labels": example["category"],
+                    "metadata": {
+                        "resolution": {
+                            "width": vid_width,
+                            "height": vid_height,
+                        },
+                        "duration": duration,
+                        "fps": fps,
+                    },
+                }
+            elif self.config.schema == "seacrowd_vidtext":
+                yield key, {
+                    "id": str(key),
+                    "video_path": os.path.join(filepath["clips"], example["vid_path"]),
+                    "text": example["label"],
+                    "metadata": {
+                        "resolution": {
+                            "width": vid_width,
+                            "height": vid_height,
+                        },
+                        "duration": duration,
+                        "fps": fps,
+                    },
+                }