Which format is the best for input images

[Rob174]

[REFLEXIONS]

• Raster images or hdf5 file faster ? Is a hdf5 file a problem for other usages ?
• Do we make a preprocessing algorithm to convert all annotations to a segmentation map and put it with the rasters in the hdf5 ?

Suggestion :

• 1 script takes as input the raster images and put them as numpy arrays in the images.hdf5
• 1 script takes as input the raster images header and put them as images_infos.json
• 1 script takes as input the annotations, creates the segmentation map from the polygons and save it into annotations_labels.hdf5

We will put the name of the raster image as the name of each dataset contained in each hdf5 file. It will allow us to access easily to data.

What is the structure of the names of raster images ?

For example, in the name S1A_IW_GRDH_1SDV_20190601T042305_20190601T042330_027481_0319CB_0EB7_NR_Cal_ML_EC_dB.data
027481_0319CB_0EB7 ensure (maybe less also does) an unique name Would it be better to use the location of the upper left pixel (for instance) as a name for each dataset in the hdf5 file ? This value can be seen twice

[Rob174]

cf #7 ok for this solution