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Tools for machine learning dataset processing

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4o3F/imagetools

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Image Tools

Batch image process tools mainly designed for dataset preprocessing

Current tools

Global args

  • thread The thread pool size for parallel operations

Common

  • crop-rectangle Crop a rectangle region of the image
  • normalize Normalize image to given range
  • map-color Map one RGB color to another in a given PNG image file
  • map-background-color Map all the non-valid color in the image to a given color
  • split-images Split large images to small pieces for augmentation purposes
  • split-images-with-bias Split large images to small pieces for augmentation purposes with bias (Bias is added between each split)
  • split-images-with-filter Split large images to small pieces with a filter for enough valid pixels
  • class2rgb Map 8 bit grayscale PNG class image to RGB image
  • rgb2class Map RGB image to 8 bit grayscale PNG class image
  • resize-images Resize all images in a given folder to a given size with a given filter
  • rgb2rle Convert RGB semantic segmentation PNG labels to RLE format
  • split-dataset Split dataset into train and test sets
  • count-classes Count class for 8 bit PNG image & Calc class balance weight
  • strip-image-edge Strip image edges
  • stich-images Stich the splited images back together
  • calc-mean-std Calc the mean and std of a dataset for normalization
  • calc-iou Calc the IoU of two images

Yolo

  • split-dataset Split dataset into train and test sets Will store result in TXT file
  • count-types Count the object number of each type in the dataset
  • rgb2yolo Convert RGB labels to YOLO TXT format

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Tools for machine learning dataset processing

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