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add LeRepairBot dataset
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metadata
license: mit
dataset_info:
  features:
    - name: guide_id
      dtype: int64
    - name: task_title
      dtype: string
    - name: device_name
      dtype: string
    - name: difficulty
      dtype: string
    - name: tools
      list: string
    - name: time_required_min
      dtype: int64
    - name: time_required_max
      dtype: int64
    - name: image_path
      dtype: image
    - name: text
      dtype: string
    - name: type
      dtype: string
  splits:
    - name: train
      num_bytes: 105039306.48
      num_examples: 4495
  download_size: 97535095
  dataset_size: 105039306.48
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Electronics Repair Dataset

A comprehensive mini dataset covering smartwatch and other wearable repair and teardown procedures.

Dataset Preview Images Categories

Dataset Overview

This dataset contains 4,649 carefully examples

Dataset Structure

Each example contains rich metadata and high-quality repair images:

{
    'guide_id': 37170,
    'task_title': 'Microsoft Band Wrist Clasp Replacement',
    'device_name': 'Microsoft Band', 
    'difficulty': 'Easy',
    'tools': ['T3 Torx Screwdriver'],
    'time_required_min': 300,
    'time_required_max': 600,
    'image_path': <PIL.Image(512, 512)>,  # High-quality repair image
    'text': 'This is a Microsoft Band Wrist Clasp Replacement guide...',
    'type': 'guide_overview'  # or 'step_instruction', 'teardown_analysis'
}

Quick Start

from datasets import load_dataset

# Load the complete dataset
dataset = load_dataset("ankithreddy/repairdataset-mini")

# Access examples
example = dataset['train'][0]
image = example['image_path']  # PIL Image object
instruction = example['text']  # Repair instruction text
device = example['device_name']  # Target device

# Filter by category
repair_guides = dataset['train'].filter(lambda x: x['type'] == 'guide_overview')
teardowns = dataset['train'].filter(lambda x: x['type'] == 'teardown_analysis')
steps = dataset['train'].filter(lambda x: x['type'] == 'step_instruction')

This dataset was created using publicly available data from here https://www.ifixit.com/api/2.0/doc for research and educational purposes only. All data belongs to iFixit and respective contributors