Help with deep learning for motorbike inspection
Data

If you are falling short of data, you obviously need to create a custom dataset i.e by labelling each part of a motorcycle. If you can collect some images, we can use a pre-trained classifier along with image augmentation technique. You can Google's Dataset Search.

To annotate your dataset, you can find tools here and here. If you need to download a number of images from Google Image Search, try this tool.

Model Architecture

Now, regarding the model, we can use any object localization algorithms to detect various parts of a motorcycle. Next, these individual parts would be fed to different models which will classify the respective faults. For detection, we can use


Faster RCNN and Mask RCNN ( semantic segmentation )
YOLO ( Lower inference time )