Datasets:
sample_id stringlengths 30 30 | video unknown | length int32 13 154 | label stringlengths 15 99 |
|---|---|---|---|
main/5535415699068794046/00001 | [
0,
0,
0,
32,
102,
116,
121,
112,
105,
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111,
109,
0,
0,
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109,
105,
115,
111,
50,
97,
118,
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49,
109,
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0,
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2,
... | 35 | WHEN YOU'RE COOKING CHIPS AT HOME |
main/5535415699068794046/00002 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAEO9dtZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 63 | THE TRADITIONAL CHIP PAN OFTEN STAYS ON THE SHELF |
main/5535415699068794046/00003 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQACkiltZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 43 | THROUGH WHAT THEY CALL A KNIFE BLOCK |
main/5535415699068794046/00004 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAEFmZtZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 65 | WHICH INVOLVES FIRING A POTATO DOWN A PIPE |
main/5535415699068794046/00006 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAEtRhtZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 68 | APART FROM THE GOLDEN COLOUR AND THE DELICIOUS FLAVOUR |
main/5535415699068794046/00007 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAExc5tZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 71 | WHAT REALLY MAKES A CHIP A CHIP IS THE CRUNCH |
main/5535415699068794046/00008 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQABZvxtZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 24 | FRESH OUT THE FRYER |
main/5535415699068794046/00009 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQACUz9tZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 39 | AS PEANUTS GROW UNDERGROUND |
main/5535415699068794046/00011 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQACmrxtZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 40 | THAT'S A HUGE AMOUNT OF MEAT |
main/5535415699068794046/00013 | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAFEMFtZGF0AAACsAYF//+s3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | 70 | I COULD LABEL THIS ON THE INGREDIENTS AS MEAT |
End of preview. Expand in Data Studio
Usage
import cv2
import torch
import datasets
from torchcodec.decoders import AudioDecoder
from torchcodec.decoders import VideoDecoder
def load_audio(source:str|bytes, start_time:int=0, end_time:int|None=None):
audio_decoder = AudioDecoder(source)
if end_time is None:
end_time = audio_decoder.metadata.duration_seconds_from_header
waveform = audio_decoder.get_samples_played_in_range(start_time, end_time).data
return waveform.transpose(1, 0) # T x 1
def load_video(source:str|bytes, start_time:int=0, end_time:int|None=None):
video_decoder = VideoDecoder(source, dimension_order="NHWC")
if end_time is None:
end_time = video_decoder.metadata.duration_seconds
vid_rgb = video_decoder.get_frames_played_in_range(start_time, end_time).data
frames = [cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY) for frame in vid_rgb.numpy()]
vid = torch.from_numpy(np.stack(frames)).unsqueeze(1)
return vid # T x C x H x W
if __name__=="__main__":
interference_speech_ds = datasets.load_dataset("MahmoodAnaam/LRS2-Interference-Speech", split="train")
sample = interference_speech_ds[0]
audio = load_audio(sample['video'])
video = load_video(sample['video'])
text = sample['label']
print(audio.shape) # T x 1
print(video.shape) # T x C x H x W
print(text)
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