Dataset Viewer
__key__
stringclasses 4
values | __url__
stringclasses 2
values | mp4
unknown | json
dict |
|---|---|---|---|
00019 | "/tmp/hf-datasets-cache/medium/datasets/86758112322626-config-parquet-and-info-ZebangCheng-test_hf_d(...TRUNCATED) | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAkRbW9vdgAAAGxtdmhkAAAAAAAAAAAAAAAAAAAD6AAABzAAAQAAAQA(...TRUNCATED) | {
"categories": "neutral",
"description": "It's me.",
"file_name": "00019.mp4",
"label": [
0
]
} |
00020 | "/tmp/hf-datasets-cache/medium/datasets/86758112322626-config-parquet-and-info-ZebangCheng-test_hf_d(...TRUNCATED) | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAGvhJtZGF0AAACrwYF//+r3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | {
"categories": "surprise",
"description": "I rember it!",
"file_name": "00020.mp4",
"label": [
1
]
} |
00021 | "/tmp/hf-datasets-cache/medium/datasets/86758112322626-config-parquet-and-info-ZebangCheng-test_hf_d(...TRUNCATED) | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAEcJFtZGF0AAACrwYF//+r3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | {
"categories": "anger",
"description": "I want go home.",
"file_name": "00021.mp4",
"label": [
2
]
} |
00022 | "/tmp/hf-datasets-cache/medium/datasets/86758112322626-config-parquet-and-info-ZebangCheng-test_hf_d(...TRUNCATED) | "AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAKozxtZGF0AAACrwYF//+r3EXpvebZSLeWLNgg2SPu73g(...TRUNCATED) | {
"categories": "fear",
"description": "I may die.",
"file_name": "00022.mp4",
"label": [
3
]
} |
test_hf_data_5
This is a video dataset in WebDataset format.
Structure
- Each
.tararchive contains video files (.mp4) and metadata (.json) with the same prefix. - The JSON files contain:
file_namelabel(numeric)categories(emotion category string)description(human annotation)
How to use
from datasets import load_dataset
ds = load_dataset("ZebangCheng/test_hf_data_5", split="train", streaming=True)
sample = next(iter(ds))
# Save video
with open(sample["json"]["file_name"], "wb") as f:
f.write(sample["mp4"])
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