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---
title: CalcTrainer Annotator
emoji: 📝
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.34.2
app_file: app.py
pinned: false
license: mit
short_description: Annotation tool for CalcTrainer handwriting dataset
dataset_info:
features:
- name: question_id
dtype: string
- name: handwriting_image
dtype: image
- name: math_problem
dtype: string
- name: correct_answer
dtype: int64
- name: ocr_prediction
dtype: string
- name: ocr_parsed_number
dtype: int64
- name: is_ocr_likely_correct
dtype: bool
- name: human_label
dtype: string
- name: was_corrected
dtype: bool
- name: annotation_status
dtype: string
splits:
- name: train
num_bytes: 4183724.125
num_examples: 1447
download_size: 4269963
dataset_size: 4183724.125
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# CalcTrainer Annotator 📝
**Annotation tool for validating OCR predictions on handwritten math answers from [CalcTrainer](https://huggingface.co/spaces/hoololi/CalcTrainer)**
## How to Use
1. **Review** the math problem and handwritten answer
2. **Validate or correct** the OCR suggestion:
- **✅ Correct** → Validates and moves to next
- **❌ Incorrect** → Type correct number and validate
3. **Export** annotations anytime to save progress
## Features
- **Smart filtering**: Only shows unannotated entries
- **OCR suggestions**: Pre-filled predictions with error warnings
- **Incremental export**: Safely add annotations without data loss
- **Progress tracking**: Real-time statistics
## Data Flow
```
CalcTrainer → Raw Dataset → Manual Annotation → Validated Dataset
```
## Output
Creates `hoololi/CalcTrainer_dataset_annotated` with human-validated labels for OCR model fine-tuning.
**Private Space** - Controlled access for annotation quality. |