Models

Saving a Model

my_model.save('model.h5')
my_model.save_weights('model_weights.h5')
!tar -cvzf model_test.tar.gz model.h5 model_weights.h5

Uploading a Model to Veda

from pyveda.models import Model
import pyveda as pv

pv.config.set_dev()

vc = pv.from_id('db3c619b-8774-4051-a330-a21771822586')

model_path = './model.tar.gz'

model = Model('XView Burkina Faso Model',
            model_path,
            library="keras",
            bounds=vc.bounds,
            mltype="object_detection",
            shape=vc.imshape,
            dtype=vc.dtype,
            training_set=vc.id)

model.save()

Deploying a Model

m = Model.from_id('930638be-a247-423a-bdca-987eb19026689')
m.deploy()

Searching for Models

from pyveda.models import search as model_search

for m in model_search():
    print(m.name, m.id)
    print('\t location:', m.location)
    print('\t lib:', m.library)
    print('\t type:', m.mltype)
    print('\t deployed', m.deployed)
    print('\t public:', m.public, '\n')

Downloading a Model

m = Model.from_id('930638be-a247-423a-bdca-987eb19026689')
m.download(path='my_local_model.tar.gz')

!ls my_local_model2.tar.gz

Predicting with Veda Models

image = MLImage(...)
AOI = [...]
model.predict(image, aoi)


model.status