Hello! I’m very new to this so please excuse any obvious mistakes.
I want to create a computer vision model in pytorch that will detect and highlight lane markers on the road using a live video feed. This is mainly for learning purposes as I know models like this already exist.
I wanted to start training with a very low count of training images because I want to make sure this all works before I spend time creating masks for more images.
I was able to train a simple segmentation model that I found online. During training, the loss was going down. Once the training finished, I tried to pass one of the training images through the model, but the results I got were unexpected.
After “denormalizing” the output mask and applying it to the input image using cv2, it was just completely blank.
Can you take a look at my code and see if anything jumps out at you as being incorrect?
Some things I can think of that might be causing this:
- Model is too simple for this task
- Not enough training data (I know this is true, but I was expecting at least some results)
- My normalization/denormalization is wrong
Thanks in advance!