Tool that makes it easy to split YOLOs images and their associated labels into separate sets for training and testing.
Project description
yolosplitter
Tool that makes it easy to split YOLOs images and their associated labels into separate sets for training and testing.
Installation
pip install yolosplitter
Uses
from yolosplitter import YoloSplitter
# give directory path containing Image and Labels
ys = YoloSplitter(input_dir="MyDataset/")
# creates the dataframe
df = ys.create_dataframe()
# saves the Images and labels in "new_dataset" dir. with data.yaml
ys.split_and_save_project(DF=df,output_dir="MyDataset-splitted",train_size=0.70)
# Dataframe contains Image names, Label names, annoations and class names.
# In the dataframe, we can observe the number of classes present in each image.
Input Directory
MyDataset/
├── 02.png
├── 02.txt
├── 03.png
├── 03.txt
├── 04.png
├── 04.txt
├── 05.png
├── 05.txt
├── 06.png
├── 06.txt
├── 07.png
├── 07.txt
├── 08.png
├── 08.txt
├── 09.png
├── 09.txt
├── 10.png
├── 10.txt
├── 11.png
└── 11.txt
Output Directory
MyDataset-splitted/
├── data.yaml
├── train
│ ├── images
│ │ ├── 03.png
│ │ ├── 04.png
│ │ ├── 05.png
│ │ ├── 07.png
│ │ ├── 08.png
│ │ ├── 09.png
│ │ └── 10.png
│ └── labels
│ ├── 03.txt
│ ├── 04.txt
│ ├── 05.txt
│ ├── 07.txt
│ ├── 08.txt
│ ├── 09.txt
│ └── 10.txt
└── val
├── images
│ ├── 02.png
│ ├── 06.png
│ └── 11.png
└── labels
├── 02.txt
├── 06.txt
└── 11.txt
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