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# Signature Detection
A simple tool to detect if there are **signatures** in **an image** or **a PDF file**.
The full documentation is presented at the [Github Repository](https://github.com/EnzoSeason/signature_detection).
## Extra Dependencies
This tool uses `Wand` to convert a PDF file into images.
`Wand` is a ctypes-based simple `ImageMagick` binding for Python. You may need to install `ImageMagick` on your local machine.
More details are available [here](https://docs.wand-py.org/en/0.6.6/).
## Usage
Signature_detect contains 4 classes.
1. Loader
2. Extractor
3. Cropper
4. Judger
### Loader
Loader can read an image or a PDF file page by page.
It returns a list of the masks. Each mask is a numpy 2 dimensions array. Its element's value is `0` or `255`.
```python
from signature_detect.loader import Loader
loader = Loader(
low_threshold=(0, 0, 250),
high_threshold=(255, 255, 255))
masks = loader.get_masks(file_path)
```
### Extractor
Extractor reads a mask, labels the regions in the mask, and removes both small and big regions. We consider that the signature is a region of middle size.
```python
from signature_detect.extractor import Extractor
extractor = Extractor(
outlier_weight=3,
outlier_bias=100,
amplfier=10,
min_area_size=10)
labeled_mask = extractor.extract(mask)
```
### Cropper
Cropper crops the regions in the labeled mask.
```python
from signature_detect.cropper import Cropper
cropper = Cropper(
min_region_size=10000,
border_ratio=0.1)
results = cropper.run(labeled_mask)
```
### Judger
Judger decides whether a region is a signature.
```python
from signature_detect.judger import Judger
judger = Judger(
size_ratio=[1, 4],
pixel_ratio=[0.01, 1])
is_signed = judger.judge(result["cropped_mask"])
```
## Dev version
If you would like to develop this package and run the tests, you can download the code and install dev environment locally.
```bash
pip install -e .[dev]
```