A tool kit for checking boxes in a dataset and visualize predictions' distribution
Project is listed under: https://pypi.org/project/ODToolkit/
To install this tool, simply
pip install Object_Detection_Toolkit
| Component | Description |
|---|---|
| Analysis() | Module for False-Positive and False-Negative analysis |
| Transformation() | Module for transformation between image xy plane and homography plane |
| Visualization() | Module for False-Positive and False-Negative visualization |
| Dataset.DatasetMaker() | Module for train/test split and sort into folders for training |
To use, simply follow belows snippet:
# ===================================
# demo for Analysis and Visualization
# ===================================
from ODToolkit import Analysis, Visualization
# get FP, FN, correct
FP, FN, correct = Analysis.get_fpfn(gt_lbl=gt_lbl, # 假定已经准备好了
pred_lbl=pred_lbl, # 假定已经准备好了
img_w=640,
img_h=480,
iou_thresh=0.25)
# visualize FP, FN, correct
visualizer = Visualization.BoxVisualizer(img_w=640, img_h=480)
visualizer.show_fpfn(FP, FN, correct, figsize=[15,10])
For unit-test, we use Behave, which provides a very flexible environment for all kinds of tests
To view a sample, go to unit_tests folder and check *.feature and steps/*.py files
To run tests, simply:
behave unit_tests/ # run all tests
behave unit_tests/xxx.feature # run particular test you want
If you want to contribute to this project, please submit a pull request with unit tests.