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@naseemap47 naseemap47 released this 17 Mar 10:08
v2.3
6ff7707

What's Changed

🛠️ Tools

11. split_data.py:

Split data into Train and Test based on ratio to YOLO Dir format

Args

-i, --image : path to image/dir
-l, --label : path to labels/dir
-s, --save : path to save splited data
-e, --exe : label exe to identify labels (txt, xml)
r, ratio : Test split ratio (0.0-1.0)

python3 tools/split_data.py -i path_to/imageDir -l path_to/labels_Dir -s path_to/split_data -e 'labels_exe' -r split_ratio

# Example:
python3 tools/split_data.py -i Data//images -l Data/labels -s data_to_train -e 'txt' -r 0.2

🛠️ Augumentaion

Augument your annotation files (Object detection) PASCAL VOC (XML) or YOLO (TXT)

  • HorizontalFlip
  • RandomScale
  • Scale
  • RandomTranslate
  • Translate
  • RandomRotate
  • Rotate
  • RandomShear
  • Shear
  • Resize
  • RandomHSV
  • Sequence

XML Augmentation

1. xml_aug.py:

Arguments:

-i, --image : path to image/dir
-x, --xml : path to xml/dir
-s, --save : path to save XML Augmentation
-y, --yaml : path to aug yaml file

Example:

python3 Augmentation/xml_aug.py -i path_to/images -x path_to/xml_labels -s path_to_save -y path_to_aug_yaml

# Example
python3 Augmentation/xml_aug.py -i Augmentation/sample/images -x Augmentation/sample/labels -s Augmentation/sample/Aug -y Augmentation/default.yaml

YOLO Augmentation (TXT)

2. txt_aug.py:

Arguments:

-i, --image : path to image/dir
-t, --txt : path to txt/dir
-s, --save : path to save YOLO(txt) Augmentation
-y, --yaml : path to aug yaml file

Example:

python3 Augmentation/txt_aug.py -i path_to/images -t path_to/txt_labels -s path_to_save -y path_to_aug_yaml

# Example
python3 Augmentation/txt_aug.py -i Augmentation/sample/images -t Augmentation/sample/labels -s Augmentation/sample/Aug -y Augmentation/default.yaml

Augmentation YAML

sample Augmentation YAML file: default.yaml

# ----------------- Augmentation Parameters -----------------
# image HSV-Hue augmentation
hsv_h: 
  hue: 100          # Range (0-179)
  prob: 0.4         # image HSV-Hue augmentation (probability)

# image HSV-Saturation augmentation
hsv_s:
  saturation: 212   # Range (0-255)
  prob: 0.7         # image HSV-Saturation augmentation (probability)

# image HSV-Value (brightness) augmentation
hsv_v:
  brightness: 120   # Range (0-255)
  prob: 0.4         # image HSV-Value (brightness) augmentation (probability)

# Mixed image HSV augmentation (Mixed HSV-Hue, HSV-Saturation and HSV-Value (brightness))
hsv:
  hue: 2          # Range (0-179)
  saturation: 2   # Range (0-255)
  brightness: 2   # Range (0-255)
  prob: 0.4       # Mixed image HSV augmentation (probability)

# image rotation
degrees:
  deg: 10         # image rotation (+/- deg)
  prob: 0.2       # image rotation (probability)

# Random image rotation
degrees_random:
  deg: 10         # image rotation range (+deg, -deg)
  prob: 0.2       # image rotation (probability)

# (float) image translation (+/- fraction)
translate:
  translate_x: 0.2
  translate_y: 0.2
  prob: 0.1

# (float) image Random translation (+/- fraction)
translate_random:
  translate: 0.2
  prob: 0.1

# (float) image scale (+/- gain)
scale:
  scale_x: 0.2
  scale_x: 0.2
  prob: 0.5

# (float) image Random scale (+/- gain)
scale_random:
  scale: 0.2
  prob: 0.5

# (float) image shear (+/- deg)
shear:
  shear: 0.2
  prob: 0.2

# (float) Random image shear (+/- deg)
shear_random:
  shear: 0.2
  prob: 0.2

flipud: 0.0 # (float) image flip up-down (probability)
fliplr: 0.5 # (float) image flip left-right (probability)
Assets 2