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I want to detect drivers with, or without seatbelts at cross roads and for that, as it is real time, I am going to use yolo algorithm. For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting images from there, I am getting images with more noise. Can I use these images for training? Also, which yolo version should I use? What are the important points that I should consider for training datasets?

I want to use any version of yolo compatible with tensorflow.

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It is much better to know basic mechanics of convnets first ,rather than diving straight into complicated models .

For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting images from there, I am getting images with more noise. Can I use these images for training? Also, which yolo version should I use? What are the important points that I should consider for training datasets?

After you are good with the theory part most of your questions will be answered , otherwise you would endup with nothing but buzzwords.

I want to use any version of yolo compatible with tensorflow.

Tensorflow is a framework for building neural networks , so in theory you can build any network with it so compatibility is not at all a problem.

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