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various cv tools, such as label tools, data augmentation, label conversion, etc.

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toolbox

Various tools for computer vision

converter

Codes for label format conversion.

  • toCOCO

    I have achieved the conversion to coco annotations including: IC15, HRSC2016, UCAS-AOS, NWPU VHR 10. and VOC. Besides, it also supports labelme annotations converted to COCO format.

  • toDOTA

The codes in this part support the conversion of data annotations from IC15, HRSC2016, UCAS-AOS, NWPU VHR 10 into polygonal form of DOTA annotations. And it also supports the preprocessing code of the corresponding datasets and the .json files generation codes.

  • toTXT

    Convert to the label format required for mAP calculation, the calculation code refers to my implementation here (for rbox).

  • toYOLO

    This part will no longer be maintained and it supports both xml and ICDAR formats.

dataset

  • DOTA_devkit

    Toolkits for DOTA datasets, with some annotations and modification attached.

  • dataset_partition

    Dataset partition for train, val, test part.
    Note: x2 means train + val, x3 means train + val + test.
    Remember to enlarge val & test set if your dataset is tiny. (such as 6:2:2)

  • subdataset_generation

    Division of subset from total dataset, used for hyperparameter adjust.
    (you can regard it as x1 dataset_partition)

  • generate_imageset

    Generate image absolute path for easy training. Supported data sets include: IC13, IC15, HRSC2016, DOTA, UCAS_AOD, NWPU_VHR, and VOC.

  • operate_on_datasets
    Operations on dataset , such as copy, label matching.

rotation

Codes for rotated object detection. Supports functions such as cuda rnms, cuda riou, python rnms, pytorch riou calculations.

data augmentation

I have implemented some data augmentations such as Affine, HSV transform, Blur, Grayscale, Gamma, RandomNoise, Sharpen, Contrast, RandomFlip. On this basis, imbalanced datasets can be automatically augmented via simple sampling strategy here.

drawbox

Useful tool for drawing bbox through providied points. The only customed part is your points obtaining function.

mAP

Support rbox evaluation and mAP calculation for object detection.

matplotlib

Provided a template for plotting 2D and 3D figure.

excel

Simple examples for excel files processing via pandas.

log_show

Visualization for training process.

spider

Easy implemention for crawling info from website.

visualization

Feature visualization tools.

Plug-and-play

  • asff-fpn
  • bam-attention

PRs are welcomed, if you have any questions, you can open an issue or contact me via [email protected].

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various cv tools, such as label tools, data augmentation, label conversion, etc.

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  • Jupyter Notebook 94.8%
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