my dataset is mixed with color and grayscale image

[shuxiao9058]

How to work with the mobile-yolo model?convert all the image to grayscale and then process with the model?

[eric612]

@shuxiao9058 , You can try force_color: true For example : https://github.com/eric612/MobileNet-YOLO/blob/master/models/yolov3_coco/mobilenet_yolov3_lite_train.prototxt

[shuxiao9058]

but the most dataset is grayscale，and the rgb channels are equal，the training result not well now.

I think convert all images to gray，and train with gray is best.

[eric612]

If the most images are grayscale , you can try to turn off image distortion , like hue,saturation , these data augmentation may confuse training

[shuxiao9058]

and also train with force color？

[shuxiao9058]

can i train with sigle channel(grayscale image),and maybe the training is faster.

[eric612]

Yes , I think it can get best performance between speed and accuracy as the few color images not much help training

[shuxiao9058]

yes,i will try.thanks for your reply.

[shuxiao9058]

another question, how to modify the model you provide to use grayscale for training?

does caffe has the force_gray param?

[eric612]

Sorry , I have not tried this way , you can try search same requirement as ssd caffe.