Here are the commands that give OK results on your datasets. Notice the centerline detection algorithm that changes between the two datasets (cropping could help to stick to one algo).
sct_deepseg_sc -i t2s_T10-L1.nii.gz -c t2s -centerline svm
sct_deepseg_gm -i t2s_T10-L1.nii.gz
sct_deepseg_sc -i t2s_T11-L2.nii.gz -c t2s -centerline cnn
sct_deepseg_gm -i t2s_T11-L2.nii.gz
Please note that on
t2s_T11-L2.nii.gz, the spinal cord is only visible at slices 7-14. Below that is the cauda equinea (i.e. only nerves), so there is nothing to segment there. The automatic segmentation only works okayish for the 3 top slices, because the scan is hampered by motion artifact and poor B1+ homogeneity (ie lack of contrast in the cord).
Also, when you crop an image is there a way to enhance the image to be able to see the GM and WM better?
No. Spatial cropping does not affect image contrast.