It's a package for resizing ALL your dataset images (into local folder) and changing the pascal_VOC coodinates in your .xml files.
- How it works?
- Warnings
- Install requirements
- Usage
- Example
- Folder structure example
- Results
- Parameters
- Walk by paths and searching by .jpg and .xml files
- Resize the image and change the XY coordinates of each object in xml file.
- Save the new files into output path. Folder structure example for more details
- If save_box_images = 1, draw the boundies box in the resized image and save it in an other file(output_path/boxes_images/))
1º: Don't worry if you have a big folder structure with many nested folders, the package will walk recursively in your dataset folder and recreate the same structure into output_path.
2º: The .jpg and .xml files must be in the same folder
pip install -r requirements.txt
python3 main.py -p <IMAGES_&_XML_PATH> --output <IMAGES_&_XML> --new_x <NEW_X_SIZE> --new_y <NEW_X_SIZE> --save_box_images <FLAG>"
python3 main.py -p /home/italojs/Pictures/dataset --output ./output --new_x 150 --new_y 150 --save_box_images 1
Look this randon folder structure with ALL my dataset
dataset
├── IMG_20181109_165212.jpg
├── IMG_20181109_165212.xml
├── IMG_20181109_165213.jpg
├── IMG_20181109_165213.xml
├── test
│ ├── IMG_20181109_163524.jpg
│ ├── IMG_20181109_163524.xml
│ ├── IMG_20181109_163525.jpg
│ └── IMG_20181109_163525.xml
├── train
│ ├── class1
│ │ ├── IMG_20181109_162519.jpg
│ │ ├── IMG_20181109_162519.xml
│ │ ├── IMG_20181109_162523.jpg
│ │ └── IMG_20181109_162523.xml
│ ├── class2
│ │ ├── IMG_20181109_162814.jpg
│ │ ├── IMG_20181109_162814.xml
│ │ ├── IMG_20181109_162818.jpg
│ │ └── IMG_20181109_162818.xml
│ ├── IMG_20181109_163315.jpg
│ ├── IMG_20181109_163315.xml
│ ├── IMG_20181109_163316.jpg
│ └── IMG_20181109_163316.xml
└── validation
├── IMG_20181109_164824.jpg
├── IMG_20181109_164824.xml
├── IMG_20181109_164825.jpg
└── IMG_20181109_164825.xml
After executed the package with:
python3 main.py -p /home/italojs/Pictures/dataset --output ./output --new_x 200 --new_y 200 --save_box_images 1
The package will resize the images, rewrite the xml files and create the same folder structure into output path with new images and xml files.
output
├── boxes_images
│ ├── boxed_IMG_20181109_165212.jpg
│ └── boxed_IMG_20181109_165213.jpg
├── IMG_20181109_165212_new.jpg
├── IMG_20181109_165212_new.xml
├── IMG_20181109_165213_new.jpg
├── IMG_20181109_165213_new.xml
├── test
│ ├── IMG_20181109_163524_new.jpg
│ ├── IMG_20181109_163524_new.xml
│ ├── IMG_20181109_163525_new.jpg
│ └── IMG_20181109_163525_new.xml
├── train
│ ├── class1
│ │ ├── IMG_20181109_162519_new.jpg
│ │ ├── IMG_20181109_162519_new.xml
│ │ ├── IMG_20181109_162523_new.jpg
│ │ └── IMG_20181109_162523_new.xml
│ ├── class2
│ │ ├── IMG_20181109_162814_new.jpg
│ │ ├── IMG_20181109_162814_new.xml
│ │ ├── IMG_20181109_162818_new.jpg
│ │ └── IMG_20181109_162818_new.xml
│ ├── IMG_20181109_163315_new.jpg
│ ├── IMG_20181109_163315_new.xml
│ ├── IMG_20181109_163316_new.jpg
│ └── IMG_20181109_163316_new.xml
└── validation
├── IMG_20181109_164824_new.jpg
├── IMG_20181109_164824_new.xml
├── IMG_20181109_164825_new.jpg
└── IMG_20181109_164825_new.xml
Here wee have the original image (650x590) an your xml:
<annotation>
<folder>imagens</folder>
<filename>IMG_20181109_165212</filename>
<path>[IMAGE_PATH]\IMG_20181109_165212.jpg</path>
<source>
<database>Unknown</database>
</source>
<size>
<width>650</width>
<height>590</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>CNH</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>74</xmin>
<ymin>192</ymin>
<xmax>267</xmax>
<ymax>499</ymax>
</bndbox>
</object>
<object>
<name>CNH</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>297</xmin>
<ymin>168</ymin>
<xmax>483</xmax>
<ymax>478</ymax>
</bndbox>
</object>
<object>
<name>CNH</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>310</xmin>
<ymin>1</ymin>
<xmax>499</xmax>
<ymax>103</ymax>
</bndbox>
</object>
</annotation>Here is the resized image (200x200) and new xml:
<annotation>
<folder>imagens</folder>
<filename>IMG_20181109_165212</filename>
<path>C:\Users\pc-casa\Music\imagens\IMG_20181109_165212.jpg</path>
<source>
<database>Unknown</database>
</source>
<size>
<width>650</width>
<height>590</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>CNH</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>17</xmin>
<ymin>49</ymin>
<xmax>62</xmax>
<ymax>127</ymax>
</bndbox>
</object>
<object>
<name>CNH</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>69</xmin>
<ymin>43</ymin>
<xmax>111</xmax>
<ymax>122</ymax>
</bndbox>
</object>
<object>
<name>CNH</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>72</xmin>
<ymin>0</ymin>
<xmax>115</xmax>
<ymax>26</ymax>
</bndbox>
</object>
</annotation>Here is a resized image (200x200), but with the boundies box drawed:
To know more about parameters use python main.py -h:
usage: main.py [-h] -p DATASET_PATH -o OUTPUT_PATH -x X -y Y
[-s SAVE_BOX_IMAGES]
optional arguments:
-h, --help show this help message and exit
-p DATASET_PATH, --path DATASET_PATH
Path to dataset data ?(image and annotations).
-o OUTPUT_PATH, --output OUTPUT_PATH
Path that will be saved the resized dataset
-x X, --new_x X The new x images size
-y Y, --new_y Y The new y images size
-s SAVE_BOX_IMAGES, --save_box_images SAVE_BOX_IMAGES
If True, it will save the resized image and a drawed
image with the boxes in the images