input.yaml

---
inputs:
  aimg_folderpath:  C:\Users\91954\Documents\GitHub\LabelMe-Image-Data-Augment-\Input_Images
  ajson_folderpath:  C:\Users\91954\Documents\GitHub\LabelMe-Image-Data-Augment-\Input_JSONS
  bgimg_folderpath:  C:\Users\91954\Documents\GitHub\LabelMe-Image-Data-Augment-\background_images
  output_folderpath:  C:\Users\91954\Desktop\seal\Freshoutput
  bg_count:  10 
  ntimes_perbg:  5
  ratio_threshold :  0.1     # Ratio of annotated area to background image area. Combinations below this ratio will be neglected.
  user_class:  default       # Specify a specific class or keep it default (takes the first annotated class) 
  pad_annotation: 5           # Amount(in pixels) of padding you want to add to the annotation (Works only on bounding box annotation)
transforms:
  scaling:
    scaling_state:  True
    downscale_prob:  0.5
    downscale_factor:  2
    upscale_prob:  0.5
    upscale_factor:  2
  rotation:
    rotation_state:  True
    rotation_prob:  0.5
    rotlimitangle:  78
  flipping:
    flipping_state:  True
    horizontal_flip_prob:  0.5
    vertical_flip_prob:  0.5
  randomshift:
    shift_state:  True
    shift_prob:  1
  blur:
    blur_state:  True
    blur_prob:  0.5
    blur_choice:  random  #0 - 'Averaging', 1 - 'Gaussian Blurring', 2 - 'Median Blurring', 3 - 'Bilateral Filtering', random - for any random blur
  noise:
    noise_state:  True
    noise_prob:  0.5
    noise_choice:  random  #0 - 'gauss', 1 - 'salt&pepper', 2 - 'poisson', 3 - 'speckle', random - for any random noise
    gauss:
      -  45          # Enter the sigma value if you have chosen gauss
      -  50       # Enter the variance value if you have chosen gauss
    salt&pepper:
      - 0.5         # Enter the s_vs_p value if you have chosen salt&pepper
      - 0.1       # Enter the amount value if you have chosen salt&pepper
    speckle:
      - 0.1         # Enter the amount value if you have chosen speckle
  grayscale:
    grayscale_state:  True
    grayscale_prob:  0.2
    grayscale_choice:  random   # 0 - grayscale the whole output image, 1 - grayscale only the annotated part in the output image, 2 - grayscale the output image except the annotated area, random - any of the three 
  brightness-contrast:
    brightness-contrast_state:  True
    brightness-contrast_prob:  0.5
    alpha:  1    # Contrast control (1.0-3.0)
    beta:  0       # Brightness control (0-100)
  edgedetection:
    edgedetection_state:  True
    edgedetection_prob:  0.2
    edgedetection_choice:  random   # 0 -  Canny Edge Detection on the whole output image, 1 - Canny Edge Detection only on the annotated part in the output image, random - any of the two