cloudflow-example.py

# Create new dataflow with Cloudflow.
flow = cloudflow.Dataflow([(‘url’, str)])

# First, apply img_preproc, then apply three models in parallel.
img = flow.map(img_preproc)
p1 = img.map(resnet_101)
p2 = img.map(vgg_16)
p3 = img.map(inception_v3)

# Combine the results with union, create a group for each input, and pick the highest confidence prediction.
flow.output = p1.union(p2, p3).groupby(rowID).agg(max, ‘conf’)

# Deploy the dataflow an execute it on an image.
flow.deploy()
flow.execute(‘s3://my_bucket/my_image’)