Enhancement of Low Light Images

[smaranjitghose]

Task:

Enhance images taken in low light conditions

Suggested workflow:

• Inside the deeppixel directory, create a new sub-directory img_undark[Please name it appropiately and use camel_case]
• In the first attempt 💭💭 use a [Jupyter notebook] to perform your work.
• Once you are done give a Pull Request🩹 with the message 📩Developed Jupyter Notebook for Enhancement of Low Light Images , briefing about your approach in the description and add a link of the above notebook in Google Colab [Please ensure you have given access] ⛔
• Once merged😎 , build a script for the same task in the img_undark 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
• Give a Pull Request 🩹 with the message 📩Developed Script for Enhancement of Low Light Images and mention how you have given the argument parameters to run the script in the description
• Once approved, work on documenting every block of code if not every line of your script
• Add a README.MD file with appropriate description [Please ensure you properly cite any research paper or blog you have taken direct reference from]
• Give another Pull Request 🩹 with a message 📩 : Documentation Updated for Enhancement of Low Light Images
• 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

References :

• Learning to see in the dark research paper

• The official implementation

• An explanatory blog

Additional Tasks:

• Curate a custom dataset 🧰 for this task
• Look for better methods to improve 🥇 this

[kritika12298]

Hello @smaranjitghose, my team 'Warriors' wants to work on this issue, please assign this to us.

[kritika12298]

I have found an IEEE paper, https://sci-hub.tw/https://ieeexplore.ieee.org/document/7351501?arnumber=7351501.
Can I implement this?

[smaranjitghose]

You can definitely start off with this and give a pull request.

However, this implementation fails in scenarios where no part of the image has additional exposure, So as a final work I would suggest going with the one I referenced earlier

[kritika12298]

Okay, will try my best!

…

On Fri, Apr 3, 2020, 21:58 Smaranjit Ghose ***@***.***> wrote: You can definitely start off with this and give a pull request. However, this implementation fails in scenarios where no part of the image has additional exposure, So as a final work I would suggest going with the one I referenced earlier — You are receiving this because you were assigned. Reply to this email directly, view it on GitHub <#70 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AOL5CD272JHRAYYUHMBXFODRKYFCZANCNFSM4L4B4HOQ> .