|
--- |
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dataset_info: |
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features: |
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- name: videoid |
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dtype: int64 |
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- name: contentUrl |
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dtype: string |
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- name: duration |
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dtype: string |
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- name: page_dir |
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dtype: string |
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- name: name |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 2993227031 |
|
num_examples: 10727607 |
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- name: validation |
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num_bytes: 1394310 |
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num_examples: 5000 |
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download_size: 1564635003 |
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dataset_size: 2994621341 |
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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: validation |
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path: data/validation-* |
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task_categories: |
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- text-to-video |
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- video-classification |
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size_categories: |
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- 10M<n<100M |
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--- |
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# Dataset Name: Video-10M |
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## Description: |
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Video-10M is a dataset consisting of 10 million videos, each accompanied by metadata including video ID, content URL, duration, page directory, and name. The dataset covers a wide range of video content, from nature scenes and outdoor activities to culinary arts and urban landscapes. It provides a diverse collection of videos suitable for various video classification tasks. |
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## Split Information: |
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- Train Split: Contains 10,727,607 samples. |
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- Validation Split: Contains 5,000 samples. |
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|
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## Features: |
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- videoid: Unique identifier for the video. |
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- contentUrl: URL or path to access the video content. |
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- duration: Duration of the video in hours, minutes, and seconds. |
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- page_dir: Directory or category associated with the video. |
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- name: Descriptive name or title for the video. |
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|
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## Usage: |
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The dataset can be used for a wide range of video classification tasks, including but not limited to content categorization, scene recognition, activity recognition, and object detection. Researchers, developers, and practitioners can leverage this dataset to train and evaluate video classification models across different domains and applications. |
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## Download |
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```python |
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from datasets import load_dataset, Dataset |
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|
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#Load the dataset |
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dataset = load_dataset("Mouwiya/Video-10M") |
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``` |
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|
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## Contact |
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**Mouwiya S. A. Al-Qaisieh** |
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[email protected] |