Once merged😎 , build a script for the same task in the img_matting directory __(If you are using Deep Learning, ensure that you have saved your trained model and its weights so that in the script you build can simply fetch it instead of training again)
Use argparse library so that the input image and the output path can be given as arguments in the terminal while running the script
Update the requirements.txt file in the root directory of the master branch to ensure any additional modules you have used in present there.
Make sure you provide sample images/videos 📷 used
Now save the model and the model weights, build a single python script that takes in an image and gives us the output (Make sure the model and model weight is properly named for future use) by using your already trained model
Task:
Enhance images taken in low light conditions
Suggested workflow:
deeppixel
directory, create a new sub-directoryimg_matting
__[Please name it appropriately and use camel_case]__Developed Jupyter Notebook for Image Matting
, briefing about your approach in the description and add a link of the above notebook in Google Colab [Please ensure you have given access] â›”img_matting
directory __(If you are using Deep Learning, ensure that you have saved your trained model and its weights so that in the script you build can simply fetch it instead of training again)requirements.txt
file in the root directory of the master branch to ensure any additional modules you have used in present there.Developed Script for Image Matting
and mention how you have given the argument parameters to run the script in the descriptionREADME.MD
file with appropriate description [Please ensure you properly cite any research paper or blog you have taken direct reference from]Documentation Updated for Image Matting
References :
The best method so far per
The official implementation
This issue is related to a fairly complex topic and hence open to everyone for the contribution!