# pie-chart-ocr
A tool to extract tabular data from pie charts, developed as a component of the CryptoSearchTools toolkit.
Note: The original repository was moved to https://git.ehtec.co/research/pie-chart-ocr.
https://github.com/ehtec/pie-chart-ocr is a mirror.
# Installation
### Install via PyPi
You can install all tagged versions of `piechartocr` from PyPi:
```commandline
python3 -m pip install --upgrade piechartocr
```
Note: You cannot run tests and examples from the PyPi installation. The required
files need to be downloaded from Gitlab.
### Build from source
Install Boost and Tesseract:
```commandline
sudo apt install libboost-system-dev tesseract-ocr build-essential git
```
Clone this repository including submodules:
```commandline
git clone --recursive https://github.com/ehtec/pie-chart-ocr.git
cd pie-chart-ocr
```
Install Python requirements:
```commandline
python3 -m pip install -r requirements.txt
```
Compile libraries:
```commandline
python3 setup.py build_ext
```
Create temporary directories:
```commandline
mkdir temp
mkdir temp1
mkdir temp2
```
Unpack test charts:
```commandline
unzip data/charts_steph.zip -d data
unzip data/charts_steph_upsampled.zip -d data
unzip data/generated_pie_charts_legend.zip -d data
unzip data/generated_pie_charts_without_legend.zip -d data
```
# Usage
Run unit tests:
```commandline
python3 -m nose2 --start-dir tests/ --with-coverage
```
Run legacy tests / examples:
```commandline
python3 run_examples.py
```
Generate test data (mock pie charts):
```commandline
python3 run_generate_test_data.py
```
To extract data from any pie chart:
```python
from piechartocr import pie_chart_ocr
# Path to pie chart
path = "/path/to/my/chart.png"
# Extract data
data = pie_chart_ocr.main(path, interactive=False)
# Print the extracted list of tuples of the form [(percentage / 100, label)]
print(data["res"])
```
# Metrics
These metrics are autogenerated by the CI-pipeline.
Metrics for mock pie charts with legend:
Metrics for mock pie charts without legend:
Metrics for real world pie charts (many of them in awful quality, some even unreadable for humans):
Raw data
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"description": "# pie-chart-ocr\nA tool to extract tabular data from pie charts, developed as a component of the CryptoSearchTools toolkit.\n\nNote: The original repository was moved to https://git.ehtec.co/research/pie-chart-ocr.\nhttps://github.com/ehtec/pie-chart-ocr is a mirror.\n\n# Installation\n\n### Install via PyPi\n\nYou can install all tagged versions of `piechartocr` from PyPi:\n\n```commandline\npython3 -m pip install --upgrade piechartocr\n```\n\nNote: You cannot run tests and examples from the PyPi installation. The required\nfiles need to be downloaded from Gitlab.\n\n### Build from source\n\nInstall Boost and Tesseract:\n\n```commandline\nsudo apt install libboost-system-dev tesseract-ocr build-essential git\n```\n\nClone this repository including submodules:\n\n```commandline\ngit clone --recursive https://github.com/ehtec/pie-chart-ocr.git\ncd pie-chart-ocr\n```\n\nInstall Python requirements:\n\n```commandline\npython3 -m pip install -r requirements.txt\n```\n\nCompile libraries:\n\n```commandline\npython3 setup.py build_ext\n```\n\nCreate temporary directories:\n```commandline\nmkdir temp\nmkdir temp1\nmkdir temp2\n```\n\nUnpack test charts:\n\n```commandline\nunzip data/charts_steph.zip -d data\nunzip data/charts_steph_upsampled.zip -d data\nunzip data/generated_pie_charts_legend.zip -d data\nunzip data/generated_pie_charts_without_legend.zip -d data\n```\n\n# Usage\n\nRun unit tests:\n\n```commandline\npython3 -m nose2 --start-dir tests/ --with-coverage\n```\n\nRun legacy tests / examples:\n\n```commandline\npython3 run_examples.py\n```\n\nGenerate test data (mock pie charts):\n\n```commandline\npython3 run_generate_test_data.py\n```\n\nTo extract data from any pie chart:\n\n```python\nfrom piechartocr import pie_chart_ocr\n\n# Path to pie chart\npath = \"/path/to/my/chart.png\"\n\n# Extract data\ndata = pie_chart_ocr.main(path, interactive=False)\n\n# Print the extracted list of tuples of the form [(percentage / 100, label)]\nprint(data[\"res\"])\n```\n\n# Metrics\n\nThese metrics are autogenerated by the CI-pipeline.\n\nMetrics for mock pie charts with legend:\n\n\n\nMetrics for mock pie charts without legend:\n\n\n\nMetrics for real world pie charts (many of them in awful quality, some even unreadable for humans):\n\n\n\n\n",
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