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test.py
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test.py
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#
# Copyright 2018-2019 IBM Corp. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import pytest
import requests
def test_swagger():
model_endpoint = 'http://localhost:5000/swagger.json'
r = requests.get(url=model_endpoint)
assert r.status_code == 200
assert r.headers['Content-Type'] == 'application/json'
json = r.json()
assert 'swagger' in json
assert json.get('info') and json.get('info').get('title') == 'MAX Object Detector'
def test_metadata():
model_endpoint = 'http://localhost:5000/model/metadata'
r = requests.get(url=model_endpoint)
assert r.status_code == 200
metadata = r.json()
model = os.getenv('MODEL')
assert metadata['id'] == f'object-detector-{model}'
assert metadata['name'] == f'{model} TensorFlow Object Detector Model'
assert metadata['description'] == f'{model} TensorFlow object detector model'
assert metadata['type'] == 'Object Detection'
assert metadata['source'] == 'https://developer.ibm.com/exchanges/models/all/max-object-detector/'
assert metadata['license'] == 'ApacheV2'
def test_predict():
model_endpoint = 'http://localhost:5000/model/predict'
file_path = 'samples/baby-bear.jpg'
with open(file_path, 'rb') as file:
file_form = {'image': (file_path, file, 'image/jpeg')}
r = requests.post(url=model_endpoint, files=file_form)
assert r.status_code == 200
response = r.json()
assert response['status'] == 'ok'
# One is Teddy Bear and the other is Child
assert frozenset((response['predictions'][0]['label_id'],
response['predictions'][1]['label_id'])) == frozenset(('1', '88'))
# Teddy Bear
bear_index = 0 if response['predictions'][0]['label_id'] == '88' else 1
assert response['predictions'][bear_index]['label_id'] == '88'
assert response['predictions'][bear_index]['label'] == 'teddy bear'
assert response['predictions'][bear_index]['probability'] > 0.95
assert response['predictions'][bear_index]['detection_box'][0] > 0.25
assert response['predictions'][bear_index]['detection_box'][0] < 0.3
assert response['predictions'][bear_index]['detection_box'][1] > 0.5
assert response['predictions'][bear_index]['detection_box'][1] < 0.6
assert response['predictions'][bear_index]['detection_box'][2] > 0.6
assert response['predictions'][bear_index]['detection_box'][2] < 0.7
assert response['predictions'][bear_index]['detection_box'][3] > 0.8
assert response['predictions'][bear_index]['detection_box'][3] < 0.9
# Child
child_index = 0 if bear_index == 1 else 1
assert response['predictions'][child_index]['label_id'] == '1'
assert response['predictions'][child_index]['label'] == 'person'
assert response['predictions'][child_index]['probability'] > 0.95
assert response['predictions'][child_index]['detection_box'][0] > 0.2
assert response['predictions'][child_index]['detection_box'][0] < 0.3
assert response['predictions'][child_index]['detection_box'][1] > 0.2
assert response['predictions'][child_index]['detection_box'][1] < 0.3
assert response['predictions'][child_index]['detection_box'][2] > 0.6
assert response['predictions'][child_index]['detection_box'][2] < 0.7
assert response['predictions'][child_index]['detection_box'][3] > 0.5
assert response['predictions'][child_index]['detection_box'][3] < 0.6
def test_predict_non_image():
model_endpoint = 'http://localhost:5000/model/predict'
file_path = 'requirements.txt'
with open(file_path, 'rb') as file:
file_form = {'image': (file_path, file, 'image/jpeg')}
r = requests.post(url=model_endpoint, files=file_form)
assert r.status_code == 400
if __name__ == '__main__':
pytest.main([__file__])