StabRise/signature_detection_v0.1

SignatureDetector

Overview

SignatureDetector is a signature detection transformer based on the YOLO ONNX model. It efficiently detects signatures in images using a pre-trained model from Hugging Face Hub. The detector is implemented as a PySpark ML transformer and can be integrated into Spark pipelines for scalable signature detection tasks in ScaleDP.

Documentation: https://scaledp.stabrise.com/en/latest/models/detectors/signature_detector.html

Model is using in: https://pdf-redaction.com/redaction/

## Usage Example

Full example notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/object-detection/3.SignatureDetection.ipynb

from scaledp import SignatureDetector, ImageDrawBoxes, PipelineModel

detector = SignatureDetector(
    keepInputData=True,
    partitionMap=True,
    numPartitions=0,
    scoreThreshold=0.25,
    task="detect",
    padding=20,
)

draw = ImageDrawBoxes(
    keepInputData=True,
    inputCols=["image", "signatures"],
    filled=False,
    color="blue",
    lineWidth=5,
    displayDataList=[],
)
# Transform the image dataframe through the signature detection stage
pipeline = PipelineModel(stages=[detector, draw])
result = pipeline.transform(image_df)

Parameters

Notes

• —The detector uses the YOLO ONNX pretrained model.
• —Supports batch processing and distributed inference with Spark.
• —Additional parameters can be set using the corresponding setter methods.