Number Plate detection Model

So lets begin with our model end to end implementation:

  1. training our model.

We have trained the model on the dataset to detect the characters in an image. this is needed since we are not detecting characters from strings but rather from images. and number-plates have slight variations too

2. Passing the video:

When we pass the video as an argument to the model. The cv2 module goes through the video frame by frame and tries to find the characters in the image that are on the number-plate. Until all the frames are completed the for loop keeps on running so that model can keep detecting new and new number-plates.

3. Exceptions which might occur:
There are chances that our model is unable to detect all the characters of number-plate in one frame so I have put a constraint that if the characters are at least more than 6 then only we need to get the output. This is vital since it reduces the useless detection where we are not able to get the data of the complete number-plate.

The model can perform only when it gets the video in the desired size and dimension so for each frame we need to fix it’s size and shape so that it can be given as an input to the model

So finally we have our detection model ready. Now lets test in on any random video. I have added a video through my GitHub profile:

To check out the complete code of Web portal where all this information will be displayed you may check out my GitHub profile link is:

THANK YOU!

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