Inspiration
When we go on vacations, we usually take many pictures, for memories of the trip. However, many of these pictures are duplicates, because sometimes we aren't satisfied with the looks of a picture. These duplicate pictures are a waste of storage because there is a better version already available. We wanted to make an easy way to remove all these duplicate pictures, and keep only the highest quality picture.
What it does
Our program compares a set of user inputted pictures, and compares their quality. They are then sorted into two different folders, one with the low quality pictures, and one with the high quality pictures. The user can then delete the low quality images to their preference.
How we built it
We built this program using python as our main backend language. Our program compares the pictures using gray scale and laplacian scale.
Challenges we ran into
The program sorted the fuzzy pictures into the blurry file, while it kept pictures that were extremely blurry into the high quality file. We fixed this by changing the numbers of the blurriness threshold.
Accomplishments that we're proud of
We learned different Python modules. We also learned a lot about photo quality and laplacian.
What we learned
During our project we learned about converting images to grayscale and using the laplacian scale. Not only this but we learned to use many different types of modules in libraries in python
What's next for Detect_Blur
We are planning to see if we can add facial recognition, and group each photo into a different file based on who is in the picture.
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