How to train darkflow for my custom object really really fast during debugging in quad core PC and without GPU? (Can I train with about 10 images and test with only those images, just to check if all convolutions are working as expected. And with 20 epoch?). There is only once class and all license plates are similar in pattern with varying in angle and its digits in plate.
I am using tiny yolo config and weight. So, what all parameters I should tune in yolo based .cfg file to do it? I feel if TV like object can be detected with same training weight and config for tiny yolo then license plate too.
Overview: I am training for object, license plate, with darkflow. I tried with about 100 custom datasets I had created. This is only for initial POC, actual implementation will have more number of images. And upon testing with test images with trained graph, object is not highlighted rather highlighting squares are shown at random location within image and random in number, starting with 2-3 square boxes to lot many number. But non of those were highlighting to the actual license plate object. It took me 20 hour of training time to verify it. I used training images for testing as well, and also a plane black screen images to test what's going on. But highlighting squares are still random in number and location even on blank screen image.