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---
license: mit
task_categories:
- image-classification
- other
language:
- en
size_categories:
- n<1K
dataset_info:
features:
- name: image
dtype: image
- name: video_segment
dtype: string
- name: transcription
dtype: string
- name: subject
dtype: string
- name: category
dtype: string
- name: subcategory
dtype: string
- name: action_description
dtype: string
- name: context_and_comments
dtype: string
splits:
- name: train
num_bytes: 0
num_examples: 54
---
# Video Dataset - consensus-01
## Dataset Description
This dataset contains video frames extracted from annotated video segments, along with annotations, transcriptions, and corresponding video clips.
## Dataset Structure
- `frames/` — extracted frames (first frame from each segment)
- `segments/` — video clips for each annotation interval
- `annotations/` — original JSON annotation
- `transcriptions/` — transcription files (`full_transcription.txt` + per segment)
- `dataset.csv` — mapping between frames, video clips, transcriptions, and metadata (subject, category, subcategory, action_description, context_and_comments)
## Dataset Statistics
- **Frames:** 54
- **Segments:** 18
- **Unique Labels:** 1
## Dataset Features
- **image**: Extracted video frame (JPEG) - first frame from each segment
- **video_segment**: Path to the corresponding video clip file
- **transcription**: Text transcription of the audio segment
- **subject**: Subject of the action (e.g., "Учитель", "Группа учеников")
- **category**: Category of the action (e.g., "Педагогические действия", "Коммуникативные модальности")
- **subcategory**: Subcategory (may contain multiple values separated by ";")
- **action_description**: Description of the action
- **context_and_comments**: Context and additional comments
## Usage
This dataset can be loaded using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
dataset = load_dataset("your-org/video-dataset-consensus-01")
```
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