Commit
•
c954cad
1
Parent(s):
1e312e6
include action recognition and multi instance retrieval
Browse files- epic_kitchens_100.py +78 -75
epic_kitchens_100.py
CHANGED
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# limitations under the License.
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# Lint as: python3
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"""
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import os
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import csv
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@@ -49,11 +53,22 @@ in the kitchen over multiple days. Annotations are collected using a novel 'Paus
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EPIC-KITCHENS-100 is an extension of the EPIC-KITCHENS dataset released in 2018, to 100 hours of footage.
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"""
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_URL_BASE = "https://raw.githubusercontent.com/epic-kitchens/epic-kitchens-100-annotations/master/"
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class EpicKitchens100(datasets.GeneratorBasedBuilder):
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""""""
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def _info(self):
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return datasets.DatasetInfo(
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@@ -64,117 +79,105 @@ class EpicKitchens100(datasets.GeneratorBasedBuilder):
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"narration_id": datasets.Value("string"),
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"participant_id": datasets.Value("string"),
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"video_id": datasets.Value("string"),
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"narration_timestamp": datasets.Value("string"),
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"start_timestamp": datasets.Value("string"),
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"stop_timestamp": datasets.Value("string"),
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# "start_frame": datasets.Value("int32"),
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# "stop_frame": datasets.Value("int32"),
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"narration": datasets.Value("string"),
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"verb": datasets.Value("string"),
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"verb_class": datasets.Value("int32"),
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"noun": datasets.Value("string"),
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"noun_class": datasets.Value("string"),
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"all_nouns": datasets.features.Sequence(datasets.Value("string")),
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"all_noun_classes": datasets.features.Sequence(datasets.Value("int32")),
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}
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),
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supervised_keys=None,
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homepage=
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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urls = {
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"
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"train": os.path.join(_URL_BASE, "EPIC_100_train.csv"),
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"validation": os.path.join(_URL_BASE, "EPIC_100_validation.csv"),
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"test": os.path.join(_URL_BASE, "EPIC_100_test_timestamps.csv"),
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},
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}
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files_path = dl_manager.download_and_extract(urls)
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"annotations": files_path[
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"split": "train",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"annotations": files_path["annotations"]["validation"],
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"split": "validation",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"annotations": files_path[
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"split": "test",
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},
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),
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]
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# }
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# return mapping
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def _generate_examples(self, annotations, split):
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"""This function returns the examples."""
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with open(annotations, encoding="utf-8") as csv_file:
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csv_reader = csv.reader(csv_file, delimiter=",")
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next(csv_reader) # Skip header
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"noun": "",
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"noun_class": -1,
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"all_nouns": [],
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"all_noun_classes": [],
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}
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# limitations under the License.
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# Lint as: python3
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"""EPIC-KITCHENS-100 is a large-scale dataset in first-person (egocentric) vision; multi-faceted, audio-visual,
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non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities
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in the kitchen over multiple days. Annotations are collected using a novel 'Pause-and-Talk' narration interface.
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EPIC-KITCHENS-100 is an extension of the EPIC-KITCHENS dataset released in 2018, to 100 hours of footage."""
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import os
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import csv
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EPIC-KITCHENS-100 is an extension of the EPIC-KITCHENS dataset released in 2018, to 100 hours of footage.
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"""
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_HOMEPAGE = "https://epic-kitchens.github.io/2022"
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_LICENSE = "CC BY-NC 4.0"
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_URL_BASE = "https://raw.githubusercontent.com/epic-kitchens/epic-kitchens-100-annotations/master/"
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_VARIANTS = [
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"action_recognition", # This split is used by four challenges: Action Recognition, Weakly supervised action recognition, Action detection, Action anticipation
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"multi_instance_retrieval",
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]
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class EpicKitchens100(datasets.GeneratorBasedBuilder):
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"""Epic Kitchens"""
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BUILDER_CONFIGS = [datasets.BuilderConfig(name) for name in _VARIANTS]
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DEFAULT_CONFIG_NAME = "action_recognition"
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def _info(self):
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return datasets.DatasetInfo(
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"narration_id": datasets.Value("string"),
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"participant_id": datasets.Value("string"),
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"video_id": datasets.Value("string"),
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"path": datasets.Value("string"),
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"narration_timestamp": datasets.Value("string"),
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"start_timestamp": datasets.Value("string"),
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"stop_timestamp": datasets.Value("string"),
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"narration": datasets.Value("string"),
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"verb": datasets.Value("string"),
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"verb_class": datasets.Value("int32"),
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# The mapping for `verb_class` is available at: https://github.com/epic-kitchens/epic-kitchens-100-annotations/blob/master/README.md#epic_100_noun_classescsv
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"noun": datasets.Value("string"),
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"noun_class": datasets.Value("string"),
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# The mapping for `noun_class` is available at: https://github.com/epic-kitchens/epic-kitchens-100-annotations/blob/master/README.md#epic_100_noun_classescsv
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"all_nouns": datasets.features.Sequence(datasets.Value("string")),
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"all_noun_classes": datasets.features.Sequence(datasets.Value("int32")),
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}
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),
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supervised_keys=None,
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homepage=_HOMEPAGE,
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citation=_CITATION,
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license=_LICENSE
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)
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def _split_generators(self, dl_manager):
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urls = {
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"action_recognition": {
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"train": os.path.join(_URL_BASE, "EPIC_100_train.csv"),
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"validation": os.path.join(_URL_BASE, "EPIC_100_validation.csv"),
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"test": os.path.join(_URL_BASE, "EPIC_100_test_timestamps.csv"),
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},
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"multi_instance_retrieval": {
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"train": os.path.join(_URL_BASE, "retrieval_annotations/EPIC_100_retrieval_train.csv"),
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"test": os.path.join(_URL_BASE, "retrieval_annotations/EPIC_100_retrieval_test.csv")
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}
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}
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files_path = dl_manager.download_and_extract(urls)
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splits = [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"annotations": files_path[self.config.name]["train"],
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"split": "train",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"annotations": files_path[self.config.name]["test"],
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"split": "test",
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},
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),
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]
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if self.config.name == "action_recognition":
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splits.append(
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"annotations": files_path[self.config.name]["validation"],
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"split": "validation",
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},
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),
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)
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return splits
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def _generate_examples(self, annotations, split):
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"""This function returns the examples."""
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with open(annotations, encoding="utf-8") as csv_file:
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csv_reader = csv.reader(csv_file, delimiter=",")
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next(csv_reader) # Skip header
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for idx, row in enumerate(csv_reader):
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narration_id, participant_id, video_id, narration_timestamp, start_timestamp, stop_timestamp = row[:6]
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if split != "test":
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# The reason why it's jumping from 5 to 8 is that we are skipping `start_frame` and `stop_frame`
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# since we are not exposing the frames, but just the videos
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narration, verb, verb_class, noun, noun_class, all_nouns, all_noun_classes = row[8:15]
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all_nouns = eval(all_nouns)
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all_noun_classes = eval(all_noun_classes)
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else:
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narration = verb = noun = ""
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verb_class = noun_class = -1
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all_nouns = all_noun_classes = []
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extended = len(narration_id.split("_")[1]) == 3
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if extended:
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path = f"EPIC-KITCHENS/{participant_id}/videos/{video_id}.MP4" #Paths for jz version
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else:
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path = f"EPIC_KITCHENS_2018/videos/{split}/{participant_id}/{video_id}.MP4" #Paths for jz version
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yield idx, {
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"extended": extended,
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"narration_id": narration_id,
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"participant_id": participant_id,
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"video_id": video_id,
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"path": path,
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"narration_timestamp": narration_timestamp,
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"start_timestamp": start_timestamp,
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"stop_timestamp": stop_timestamp,
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"narration": narration,
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"verb": verb,
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"verb_class": verb_class,
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"noun": noun,
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"noun_class": noun_class,
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"all_nouns": all_nouns,
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"all_noun_classes": all_noun_classes,
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}
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