| ---
|
| license: mit
|
| task_categories:
|
| - image-to-text
|
| language:
|
| - en
|
| tags:
|
| - handwritten-digits
|
| - math-education
|
| - ocr
|
| - optical-character-recognition
|
| - handwriting-recognition
|
| size_categories:
|
| - n<1K
|
| configs:
|
| - config_name: default
|
| data_files:
|
| - split: train
|
| path: data/train-*
|
| dataset_info:
|
| features:
|
| - name: session_id
|
| dtype: string
|
| - name: question_id
|
| dtype: string
|
| - name: timestamp
|
| dtype: string
|
| - name: operand_a
|
| dtype: int64
|
| - name: operand_b
|
| dtype: int64
|
| - name: operation
|
| dtype: string
|
| - name: correct_answer
|
| dtype: int64
|
| - name: difficulty
|
| dtype: string
|
| - name: ocr_prediction
|
| dtype: string
|
| - name: ocr_parsed_number
|
| dtype: int64
|
| - name: is_correct
|
| dtype: bool
|
| - name: ocr_model_name
|
| dtype: string
|
| - name: ocr_processing_time
|
| dtype: float64
|
| - name: ocr_confidence
|
| dtype: float64
|
| - name: session_duration
|
| dtype: int64
|
| - name: session_total_questions
|
| dtype: int64
|
| - name: app_version
|
| dtype: string
|
| - name: hardware
|
| dtype: string
|
| - name: handwriting_image
|
| dtype: image
|
| - name: session_accuracy
|
| dtype: float64
|
| - name: session_total_ocr_time
|
| dtype: float64
|
| - name: session_avg_ocr_time
|
| dtype: float64
|
| splits:
|
| - name: train
|
| num_bytes: 4576695.625
|
| num_examples: 1475
|
| download_size: 4403834
|
| dataset_size: 4576695.625
|
| ---
|
|
|
| # CalcTrainer Dataset 🧮
|
|
|
| Handwritten mathematical answers collected from the [CalcTrainer](https://huggingface.co/spaces/hoololi/CalcTrainer) interactive math training application.
|
|
|
| ## Dataset Fields
|
|
|
| ### Core Data
|
| | Field | Type | Description |
|
| |-------|------|-------------|
|
| | `handwriting_image` | Image | Handwritten answer image (~100x100px) |
|
| | `ocr_prediction` | string | Raw OCR output text |
|
| | `ocr_parsed_number` | int32 | Cleaned numeric value from OCR |
|
| | `is_correct` | bool | Whether OCR matches correct answer |
|
|
|
| ### Mathematical Context
|
| | Field | Type | Description |
|
| |-------|------|-------------|
|
| | `operand_a` | int32 | First number (e.g., 7 in "7 × 3") |
|
| | `operand_b` | int32 | Second number (e.g., 3 in "7 × 3") |
|
| | `operation` | string | Operation: `+`, `-`, `×`, `÷` |
|
| | `correct_answer` | int32 | Expected correct answer |
|
| | `difficulty` | string | `Facile` (Easy) or `Difficile` (Hard) |
|
|
|
| ### OCR Metrics
|
| | Field | Type | Description |
|
| |-------|------|-------------|
|
| | `ocr_model_name` | string | OCR model used (e.g., "microsoft/trocr-base-handwritten") |
|
| | `ocr_processing_time` | float32 | Processing time in seconds |
|
| | `hardware` | string | Hardware used for OCR |
|
|
|
| ### Session Info
|
| | Field | Type | Description |
|
| |-------|------|-------------|
|
| | `session_id` | string | Unique session identifier |
|
| | `question_id` | string | Unique question identifier |
|
| | `timestamp` | string | When the session was completed |
|
| | `session_duration` | int32 | Session length (30 or 60 seconds) |
|
| | `session_accuracy` | float32 | Overall session accuracy percentage |
|
| | `session_avg_ocr_time` | float32 | Average OCR time per image in session |
|
|
|
| ## Usage
|
|
|
| ```python
|
| from datasets import load_dataset
|
|
|
| dataset = load_dataset("hoololi/CalcTrainer_dataset")
|
| train_data = dataset["train"]
|
|
|
| # Example: Access first item
|
| item = train_data[0]
|
| print(f"Math problem: {item['operand_a']} {item['operation']} {item['operand_b']} = {item['correct_answer']}")
|
| print(f"OCR predicted: '{item['ocr_prediction']}' → {item['ocr_parsed_number']}")
|
| print(f"Correct: {item['is_correct']}")
|
| ```
|
|
|
| ## Data Source
|
|
|
| Real handwriting samples from users solving math problems in the CalcTrainer application. Users write answers on a digital canvas during timed math sessions.
|
|
|
| **Generated from**: [CalcTrainer Interactive Math Training](https://huggingface.co/spaces/hoololi/CalcTrainer) 🧮 |
