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Hello guys,

I'm learning how to train the cascade classifier for object detection, I have sample project I trained from a car dataset and it works ok.

Now I would like to create my own classifier to detect a specific object of my choice. I plan on taking some videos of the object in different backgrounds (positives) and some random videos of backgrounds without the objects (negatives).

My questions is, once I extract the images from the videos I take:

• Do I have to convert the colour images to gray scale?
• Do I have to resize the images to make them smaller?
• When I train the classifier and creating the vector file, what size should I use for the width and height? Should I use the actual image size or something else?

Thank you!

Hello guys,

I'm learning how to train the cascade classifier for object detection, I have sample project I trained from a car dataset and it works ok.

Now I would like to create my own classifier to detect a specific object of my choice. I plan on taking some videos of the object in different backgrounds (positives) and some random videos of backgrounds without the objects (negatives).

My questions is, once I extract the images from the videos I take:

• Do I have to convert the colour images to gray scale?
• Do I have to resize the images to make them smaller?
• When I train the classifier and creating the vector file, what size should I use for the width and height? Should I use the actual image size or something else?

Thank you!