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Duplicate from flwrlabs/ucf101

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Co-authored-by: Adam Narożniak <adamnarozniak@users.noreply.huggingface.co>

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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.tgz filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ *.pcm filter=lfs diff=lfs merge=lfs -text
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+ *.sam filter=lfs diff=lfs merge=lfs -text
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+ *.raw filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - compressed
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+ *.aac filter=lfs diff=lfs merge=lfs -text
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+ *.flac filter=lfs diff=lfs merge=lfs -text
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+ *.mp3 filter=lfs diff=lfs merge=lfs -text
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+ *.ogg filter=lfs diff=lfs merge=lfs -text
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+ *.wav filter=lfs diff=lfs merge=lfs -text
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+ # Image files - uncompressed
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+ *.bmp filter=lfs diff=lfs merge=lfs -text
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+ *.gif filter=lfs diff=lfs merge=lfs -text
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+ *.png filter=lfs diff=lfs merge=lfs -text
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+ *.tiff filter=lfs diff=lfs merge=lfs -text
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+ # Image files - compressed
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+ *.jpg filter=lfs diff=lfs merge=lfs -text
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+ *.jpeg filter=lfs diff=lfs merge=lfs -text
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+ *.webp filter=lfs diff=lfs merge=lfs -text
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1
+ ---
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+ dataset_info:
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+ features:
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+ - name: image
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+ dtype: image
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+ - name: video_id
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+ dtype: string
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+ - name: clip_id
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+ dtype: string
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+ - name: frame
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+ dtype: int64
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+ - name: label
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+ dtype:
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+ class_label:
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+ names:
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+ '0': ApplyEyeMakeup
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+ '1': ApplyLipstick
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+ '2': Archery
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+ '3': BabyCrawling
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+ '4': BalanceBeam
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+ '5': BandMarching
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+ '6': BaseballPitch
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+ '7': Basketball
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+ '8': BasketballDunk
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+ '9': BenchPress
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+ '10': Biking
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+ '11': Billiards
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+ '12': BlowDryHair
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+ '13': BlowingCandles
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+ '14': BodyWeightSquats
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+ '15': Bowling
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+ '16': BoxingPunchingBag
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+ '17': BoxingSpeedBag
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+ '18': BreastStroke
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+ '19': BrushingTeeth
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+ '20': CleanAndJerk
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+ '21': CliffDiving
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+ '22': CricketBowling
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+ '23': CricketShot
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+ '24': CuttingInKitchen
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+ '25': Diving
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+ '26': Drumming
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+ '27': Fencing
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+ '28': FieldHockeyPenalty
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+ '29': FloorGymnastics
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+ '30': FrisbeeCatch
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+ '31': FrontCrawl
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+ '32': GolfSwing
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+ '33': Haircut
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+ '34': HammerThrow
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+ '35': Hammering
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+ '36': HandstandPushups
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+ '37': HandstandWalking
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+ '38': HeadMassage
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+ '39': HighJump
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+ '40': HorseRace
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+ '41': HorseRiding
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+ '42': HulaHoop
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+ '43': IceDancing
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+ '44': JavelinThrow
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+ '45': JugglingBalls
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+ '46': JumpRope
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+ '47': JumpingJack
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+ '48': Kayaking
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+ '49': Knitting
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+ '50': LongJump
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+ '51': Lunges
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+ '52': MilitaryParade
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+ '53': Mixing
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+ '54': MoppingFloor
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+ '55': Nunchucks
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+ '56': ParallelBars
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+ '57': PizzaTossing
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+ '58': PlayingCello
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+ '59': PlayingDaf
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+ '60': PlayingDhol
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+ '61': PlayingFlute
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+ '62': PlayingGuitar
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+ '63': PlayingPiano
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+ '64': PlayingSitar
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+ '65': PlayingTabla
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+ '66': PlayingViolin
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+ '67': PoleVault
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+ '68': PommelHorse
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+ '69': PullUps
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+ '70': Punch
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+ '71': PushUps
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+ '72': Rafting
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+ '73': RockClimbingIndoor
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+ '74': RopeClimbing
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+ '75': Rowing
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+ '76': SalsaSpin
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+ '77': ShavingBeard
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+ '78': Shotput
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+ '79': SkateBoarding
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+ '80': Skiing
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+ '81': Skijet
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+ '82': SkyDiving
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+ '83': SoccerJuggling
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+ '84': SoccerPenalty
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+ '85': StillRings
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+ '86': SumoWrestling
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+ '87': Surfing
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+ '88': Swing
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+ '89': TableTennisShot
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+ '90': TaiChi
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+ '91': TennisSwing
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+ '92': ThrowDiscus
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+ '93': TrampolineJumping
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+ '94': Typing
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+ '95': UnevenBars
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+ '96': VolleyballSpiking
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+ '97': WalkingWithDog
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+ '98': WallPushups
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+ '99': WritingOnBoard
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+ '100': YoYo
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+ splits:
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+ - name: train
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+ num_bytes: 31974277609.664
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+ num_examples: 1786096
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+ - name: test
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+ num_bytes: 14764935697.708
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+ num_examples: 697222
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+ download_size: 54505499695
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+ dataset_size: 46739213307.372
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: test
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+ path: data/test-*
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+ license: unknown
134
+ ---
135
+ # Dataset Card for UCF101
136
+
137
+ UCF101 is an action recognition data set of realistic action videos collected from YouTube, having 101 action categories. This version of the dataset does not contain images but images saved frame by frame. Train and test splits are generated based on the authors' first version train/test list.
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+
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+ ## Dataset Details
140
+
141
+ The UCF101 includes 13320 videos from 101 action categories. For more details, visit the website and the publication specified below.
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+
143
+ ### Dataset Sources
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+
145
+ - **Paper:** https://arxiv.org/abs/1212.0402
146
+ - **Website** https://www.crcv.ucf.edu/data/UCF101.php
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+
148
+ ## Uses
149
+
150
+ In order to prepare the dataset for the FL settings, we recommend using [Flower Dataset](https://flower.ai/docs/datasets/) (flwr-datasets) for the dataset download and partitioning and [Flower](https://flower.ai/docs/framework/) (flwr) for conducting FL experiments.
151
+
152
+ To partition the dataset, do the following.
153
+ 1. Install the package.
154
+ ```bash
155
+ pip install flwr-datasets[vision]
156
+ ```
157
+ 2. Use the HF Dataset under the hood in Flower Datasets.
158
+ ```python
159
+ from flwr_datasets import FederatedDataset
160
+ from flwr_datasets.partitioner import NaturalIdPartitioner
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+
162
+ fds = FederatedDataset(
163
+ dataset="flwrlabs/ucf101",
164
+ partitioners={"train": NaturalIdPartitioner(partition_by="video_id")}
165
+ )
166
+ partition = fds.load_partition(partition_id=0)
167
+ ```
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+
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+ ## Dataset Structure
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+
171
+ ### Data Instances
172
+ The first instance of the train split is presented below:
173
+ ```
174
+ {'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=320x240>,
175
+ 'video_id': 'v_ApplyEyeMakeup_g08',
176
+ 'clip_id': 'v_ApplyEyeMakeup_g08_c01',
177
+ 'frame': 1,
178
+ 'label': 0}
179
+ ```
180
+ ### Data Split
181
+
182
+ ```
183
+ DatasetDict({
184
+ train: Dataset({
185
+ features: ['image', 'video_id', 'clip_id', 'frame', 'label'],
186
+ num_rows: 1786096
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+ })
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+ test: Dataset({
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+ features: ['image', 'video_id', 'clip_id', 'frame', 'label'],
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+ num_rows: 697222
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+ })
192
+ })
193
+ ```
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+
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+ ## Citation
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+
197
+ When working with the Ambient Acoustic Context dataset, please cite the original paper.
198
+ If you're using this dataset with Flower Datasets and Flower, cite Flower.
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+
200
+ **BibTeX:**
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+
202
+ Original paper:
203
+ ```
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+ @misc{soomro2012ucf101dataset101human,
205
+ title={UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild},
206
+ author={Khurram Soomro and Amir Roshan Zamir and Mubarak Shah},
207
+ year={2012},
208
+ eprint={1212.0402},
209
+ archivePrefix={arXiv},
210
+ primaryClass={cs.CV},
211
+ url={https://arxiv.org/abs/1212.0402},
212
+ }
213
+ ````
214
+
215
+ Flower:
216
+
217
+ ```
218
+ @article{DBLP:journals/corr/abs-2007-14390,
219
+ author = {Daniel J. Beutel and
220
+ Taner Topal and
221
+ Akhil Mathur and
222
+ Xinchi Qiu and
223
+ Titouan Parcollet and
224
+ Nicholas D. Lane},
225
+ title = {Flower: {A} Friendly Federated Learning Research Framework},
226
+ journal = {CoRR},
227
+ volume = {abs/2007.14390},
228
+ year = {2020},
229
+ url = {https://arxiv.org/abs/2007.14390},
230
+ eprinttype = {arXiv},
231
+ eprint = {2007.14390},
232
+ timestamp = {Mon, 03 Aug 2020 14:32:13 +0200},
233
+ biburl = {https://dblp.org/rec/journals/corr/abs-2007-14390.bib},
234
+ bibsource = {dblp computer science bibliography, https://dblp.org}
235
+ }
236
+ ```
237
+
238
+ ## Dataset Card Contact
239
+
240
+ In case of any doubts about the dataset preprocessing and preparation, please contact [Flower Labs](https://flower.ai/).
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