Mask-RCNN project
A pre-trained model is a model that has been trained usually with a big dataset using big computers and can be fine-tuned for a given problem using small amounts of computation. This is possible to do with Deep Learning, where training a model consists in adjusting some matrices of weights. When we refer to pre-trained weights we mean that we train a model with big datasets and then we store the weights in order to be used by other' tasks.
I am currently doing a group project about Semantic Segmentation and need to train model with own data set. The problem is  data set is not available in any pre-trained model since the objective is to detect each part of sneakers(eg. lace, outsole, front patch, logos etc). None of our team members had never studied deep learning but had studied in computer science.
Also, there's another question about Mask-RCNN. What is the exact meaning of weights of pre-trained model? Is it the weights calculated from DL model?