FLETA Hosted AMA with CryptoDaku

FLETA hosted AMA with CryptoDaku. Many community members of CryptoDaku asked diverse questions about FLETA, and here we share some of those questions. Before we start AMA, we would love to know about…

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Fun and Failure with Computer Vision Tools

The goal of the project was to see if I can apply computer vision techniques to the real estate industry. Couple of thoughts in my mind:

The tools mainly used here are: Python, Kaggle Kernel, OpenCV, EasyOCR, Imutils(for manipulation of images)

It was super cool to see the different libraries work together. All credit goes to Nicholas Renotte’s project for showing the steps.:

Using OpenCV for changing up the image to find the edges
Isolating just the number plate
Seeing this happen was really cool
The shape is not rectangular enough is my guess
The muffler!

2. Limitations: Shapes are very important. If I extrapolated this to houses, bricks get in the way of the code. There is probably a higher level workaround I am not aware of.

Good ol’ brick! lol

3. Limitation: Greyscale can be detrimental based on origional picture quality

pretty clear here
After filter, the license plate kind of goes away, changing the params helped a bit but overall, the code was having trouble picking up the proper contours for a rectangle
It finds a random rectangle, which is ok. I checked the array of all contour combinations and the license plate was not one of them.
I got a good feeling about this!
fingers crossed!
uh oh
This is totally the license plate

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