In the python utils.py file, the minimum components to analyze with PCA seems to be 1024. Why not use default sklearn setting PCA would use all 2800 samples, any reason to stick to 1024. This would also mean that if you have 1024+ samples(images ) you would always calculate the results only for 1024 PCs. Any reason for this choice? Am I missing something?
In the python
utils.py file, the minimum components to analyze with PCA seems to be 1024. Why not use default sklearn setting PCA would use all 2800 samples, any reason to stick to 1024. This would also mean that if you have 1024+ samples(images ) you would always calculate the results only for 1024 PCs. Any reason for this choice? Am I missing something?