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Datasets:
bitsydarel
/
computer-use-large

Tasks:
Video Classification
Robotics
Languages:
English
Size:
10K<n<100K
Tags:
screen-recording
computer-use
software-tutorials
gui
desktop
License:
Dataset card Files
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bitsydarel ShadowPenguin commited on
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Duplicate from markov-ai/computer-use-large

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Co-authored-by: Dev Mandal <ShadowPenguin@users.noreply.huggingface.co>

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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.h5 filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.lz4 filter=lfs diff=lfs merge=lfs -text
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+ *.mds filter=lfs diff=lfs merge=lfs -text
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+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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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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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ # Audio files - compressed
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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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+ *.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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+ *.jpeg filter=lfs diff=lfs merge=lfs -text
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+ *.webp filter=lfs diff=lfs merge=lfs -text
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+ # Video files - compressed
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - video-classification
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+ - robotics
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+ language:
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+ - en
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+ tags:
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+ - screen-recording
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+ - computer-use
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+ - software-tutorials
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+ - gui
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+ - desktop
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+ size_categories:
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+ - 10K<n<100K
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+ configs:
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+ - config_name: autocad
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+ data_files:
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+ - split: train
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+ path:
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+ - data/autocad/*
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+ - data/autocad_2/*
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+ - config_name: blender
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+ data_files:
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+ - split: train
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+ path:
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+ - data/blender/*
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+ - data/blender_2/*
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+ - config_name: excel
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+ data_files:
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+ - split: train
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+ path: data/excel/*
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+ - config_name: photoshop
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+ data_files:
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+ - split: train
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+ path:
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+ - data/photoshop/*
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+ - data/photoshop_2/*
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+ - config_name: salesforce
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+ data_files:
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+ - split: train
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+ path: data/salesforce/*
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+ - config_name: vscode
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+ data_files:
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+ - split: train
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+ path: data/vscode/*
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+ ---
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+
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+ # Computer Use Large
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+
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+ A large-scale dataset of **48,478 screen recording videos** (~12,300 hours) of professional software being used, sourced from the internet. All videos have been trimmed to remove non-screen-recording content (intros, outros, talking heads, transitions) and audio has been stripped.
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+
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+ ## Dataset Summary
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+
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+ | Category | Videos | Hours |
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+ |---|---|---|
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+ | AutoCAD | 10,059 | 2,149 |
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+ | Blender | 11,493 | 3,624 |
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+ | Excel | 8,111 | 2,002 |
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+ | Photoshop | 10,704 | 2,060 |
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+ | Salesforce | 7,807 | 2,336 |
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+ | VS Code | 304 | 127 |
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+ | **Total** | **48,478** | **~12,300** |
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+
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+ ## Data Fields
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+
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+ Each folder contains a `metadata.jsonl` file with the following fields per video:
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+
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+ | Field | Type | Description |
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+ |---|---|---|
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+ | `file_name` | string | Filename of the video (e.g. `abc123.mp4`) |
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+ | `category` | string | Software category |
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+ | `trimmed_duration` | float | Duration of the video in seconds |
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+ | `num_segments` | int | Number of contiguous screen recording segments |
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+
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+ ## Data Organization
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+
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+ Videos are stored under `data/{category}/` with a `metadata.jsonl` per folder. Due to HuggingFace's 10,000 file per directory limit, some categories are split across two folders (e.g. `blender/` and `blender_2/`).
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+
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+ ```
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+ data/
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+ autocad/ (9,999 videos + metadata.jsonl)
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+ autocad_2/ (60 videos + metadata.jsonl)
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+ blender/ (9,999 videos + metadata.jsonl)
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+ blender_2/ (1,494 videos + metadata.jsonl)
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+ excel/ (8,111 videos + metadata.jsonl)
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+ photoshop/ (9,999 videos + metadata.jsonl)
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+ photoshop_2/ (705 videos + metadata.jsonl)
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+ salesforce/ (7,807 videos + metadata.jsonl)
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+ vscode/ (304 videos + metadata.jsonl)
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+ ```
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load a specific category
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+ ds = load_dataset("markov-ai/computer-use-large", "blender")
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+
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+ # Load all categories
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+ ds = load_dataset("markov-ai/computer-use-large")
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+ ```
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+
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+ ## Intended Use
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+
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+ This dataset is designed for training and evaluating computer use agents — models that interact with desktop software through GUI actions (clicking, typing, scrolling). The screen recordings provide demonstrations of real software workflows across diverse applications.
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+
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+ ## License
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+
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+ CC-BY-4.0
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