Open Source Ecosystems

Installation

Install onemetric from PyPI (recommended):

pip install --upgrade pip
pip install onemetric

Install onemetric from the GitHub source:

git clone https://github.com/SkalskiP/onemetric.git
cd onemetric
python setup.py install

Example

Figure 1. Dataset sample, blue - ground-truth and red - detection.

Calculate [email protected]

>>> from onemetric.cv.loaders import YOLOLoader
>>> from onemetric.cv.object_detection import MeanAveragePrecision

>>> model = load_model(...)  # model-specific loading method

>>> data_set = YOLOLoader(
...     images_dir_path=DATA_SET_IMAGES_PATH, 
...     annotations_dir_path=DATA_SET_ANNOTATIONS_PATH
... ).load()

>>> true_batches, detection_batches = [], []
>>> for entry in data_set:
>>>     detections = model(entry.get_image())  # model-specific prediction method
>>>     true_batches.append(entry.get_annotations())
>>>     detection_batches.append(detections)

>>> mean_average_precision = MeanAveragePrecision.from_detections(
...     true_batches=true_batches, 
...     detection_batches=detection_batches, 
...     num_classes=12,
...     iou_threshold=0.5
... )

>>> mean_average_precision.value
0.61

Calculate Confusion Matrix



>>> confusion_matrix = ConfusionMatrix.from_detections(
...     true_batches=true_batches, 
...     detection_batches=detection_batches,
...     num_classes=12
... )

>>> confusion_matrix.plot(CONFUSION_MATRIX_TARGET_PATH, class_names=CLASS_NAMES)

Figure 2. Create confusion matrix chart

Documentation

The official documentation is hosted on Github Pages: https://skalskip.github.io/onemetric

Contribute

Feel free to file issues or pull requests. Let us know what metrics should be part of onemetric!

Citation

Please cite onemetric in your publications if this is useful for your research. Here is an example BibTeX entry:

@MISC{onemetric,
   author = {Piotr Skalski},
   title = {{onemetric}},
   howpublished = "\url{https://github.com/SkalskiP/onemetric/}",
   year = {2021},
}