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alexcasalboni/classify.py

Last active August 29, 2015 14:20
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AWS ML Online prediction
Raw
classify.py
import boto3
from boto3.session import Session
#AWS config
session = Session(aws_access_key_id='YOUR_KEY', aws_secret_access_key='YOUR_SECRET_KEY')
machinelearning = session.client('machinelearning', region_name='YOUR_REGION')
model_id = 'YOUR_MODEL_ID'
labels = {'1': 'walking', '2': 'walking upstairs', '3': 'walking downstairs', '4': 'sitting', '5': 'standing', '6': 'laying'}
try:
#dynamically retrieve model and prediction endpoint
model = machinelearning.get_ml_model(MLModelId=model_id)
prediction_endpoint = model.get('EndpointInfo').get('EndpointUrl')
#read online record from file
with open('record.csv') as f:
record_str = f.readline()
#convert csv format to dict with Var00N indexes
record = {}
for index,val in enumerate(record_str.split(',')):
record['Var%03d' % (index+1)] = val #values must be strings (i.e. {"Var001": "0.5"})
#retrieve online prediction
response = machinelearning.predict(MLModelId=model_id, Record=record, PredictEndpoint=prediction_endpoint)
label = response.get('Prediction').get('predictedLabel')
print("You are currently %s." % labels[label])
except Exception as e:
print(e)
Raw
record.csv
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