A GUI wrapper created by DearPyGui for pre-processing images to generate templates that are used as dataset.
- Use FFmpeg to separate videos to images for further processing.
- Use U^2-Net to make YCB like dataset.
The source codes have been tested with python3.8
,
and the packages needed are written into the requirements.txt
.
You can just use git clone https://github.com/ar-mine/IMG_Automator.git
to download the whole repo.
- Modify the
main.py
to specify useconfig-win.yaml
orconfig.yaml
and then runmain.py
.- It will load pre-trained
U^2-Net
model and then load config file if it exists. - Put your video that contains target objects in the path of
video folder
and then clickseparate
button, then the video will be separated into sequence images according to the rate of slider. - Or you can just put all images in
input folder
and clickprocess
button, then it will generate images only contain target and save them intemp folder
. - Finally, YCB-like images dataset will be saved in
result folder
with resolution of 120*120. - You can use
open
to see the images in the folder and useclean
and related checkbox to clean redundant images or videos (the action will eraser the whole folder specified except the folder itself).
- It will load pre-trained
- The
config-win.yaml
andconfig.yaml
store the default processing paths based on different formats of Windows and Linux. You can change it according to your project or modify the path while running the program.
Test video link: https://drive.google.com/file/d/17pofu-ii4KtUTX7YxbwOes9vlHXXils3/view?usp=sharing.
By default, you can put the video in the IMG_Automator\dataset\video
folder.