You can answer all the theoretical questions and, perhaps more importantly, struggle to solve all the code challenges that each exercise contains:
- In the Getting the data section, a filtering function was applied to the PASCAL VOC 2007 dataset to select only the images with a single object inside. The filtering process, however, doesn't take into account the class balancement.
Create a function that, given the three filtered datasets, merges them first and then creates three balanced splits (with a tolerable class imbalance, if it is not possible to have them perfectly balanced). - Use the splits created in the previous point to retrain the network for localization and classification defined in the chapter. How and why do the performances change?
- What measures the Intersection over Union metric?
- What does an IoU value of 0.4 represent? A good or a bad match?
- What...
