def test_fail_prediction_by_invalid_model_type(self):
with self.assertRaises(InvalidMessage):
messagebus.handle(
commands.MakePrediction(
image_path=os.path.join(ROOT_DIR, 'tests', 'data',
'sample.jpg'),
model_type='invalid',
))
def test_raise_error_if_topk_is_negative(self):
with self.assertRaises(ValueError):
messagebus.handle(
commands.MakePrediction(
image_path=os.path.join(ROOT_DIR, 'tests', 'data',
'sample.jpg'),
model_type='fake',
topk=-3,
))
def test_raise_error_due_to_wrong_image_format_when_predicting(self):
fp = tempfile.NamedTemporaryFile()
fp.write(b'non-image data')
with self.assertRaises(InvalidImageDataFormat):
messagebus.handle(
commands.MakePrediction(
image_path=fp.name,
model_type='fake',
), )
def upload_image_file_object(img_file):
"""Read image file data and save to Database if valid.
Return error if the given file is invalid.
"""
if img_file:
try:
encode = messagebus.handle(
commands.UploadImage(file_object=img_file))
except Exception as e:
kwargs = {'status': 'error', 'message': 'failed to save image'}
if config.DEBUG: # pragma: no cover
logger.error(traceback.format_exc())
else: # pragma: no cover
logger.error(e)
status_code = 400
else:
kwargs = {'status': 'success', 'imgId': encode}
status_code = 201
else: # pragma: no cover
if config.DEBUG:
logger.error('Counld not find image')
kwargs = {'status': 'error', 'message': 'failed to upload image'}
status_code = 400
return kwargs, status_code
def test_run_prediction(self):
pred = messagebus.handle(
commands.MakePrediction(
image_path=os.path.join(ROOT_DIR, 'tests', 'data',
'sample.jpg'),
model_type='fake',
))
self.assertTrue(isinstance(pred, np.ndarray))
def test_get_labels_with_prediction(self):
result = messagebus.handle(
commands.MakePrediction(
image_path=os.path.join(ROOT_DIR, 'tests', 'data',
'sample.jpg'),
model_type='fake',
topk=3,
))
self.assertEqual(len(result), 3)
def test_add_label_to_prediction_result(self):
data = np.random.randint(1, 100,
len(FakeLabelData.labels)).astype(np.float32)
data /= data.sum()
result = messagebus.handle(
commands.LabelPrediction(prediction=data,
model_type='fake',
topk=2))
self.assertEqual(len(result), 2)
def fetch_label_list(model_type):
try:
label_list = messagebus.handle(
commands.FetchLabels(model_type=model_type))
except InvalidMessage:
return {'status': 'error', 'message': 'Invalid model type'}, 400
kwargs = {'status': 'success', 'labelList': label_list}
response = jsonify(**kwargs)
response.status_code = 200
return response
def predict_image(model_type):
"""Predict image from a provided file.
The output format is:
{
status: str
imgId: str
result: List
}
"""
img_file = request.files['file']
kwargs, status_code = upload_image_file_object(img_file)
if status_code == 201:
try:
model = Image.get_by_encoded_id(kwargs.get('imgId'))
filepath = os.path.join(config.STATIC_DIR, config.UPLOAD_DIR,
model.filename)
result = messagebus.handle(
commands.MakePrediction(
image_path=filepath,
model_type=model_type,
topk=3,
))
# convert float to percentages to display to be readable
result = list(map(serialize_predict_result, result))
kwargs['result'] = result
except Exception as e:
if config.DEBUG: # pragma: no cover
logger.error(traceback.format_exc())
else: # pragma: no cover
logger.error(e)
kwargs = {
'status': 'error',
'message': 'a problem occured during prediction'
}
status_code = 500
response = jsonify(kwargs)
response.status_code = status_code
return response
def test_fetch_labels_by_invalid_model_type(self):
with self.assertRaises(InvalidMessage):
messagebus.handle(commands.FetchLabels(model_type='invalid'))
def test_fetch_all_label_items(self):
labels = messagebus.handle(commands.FetchLabels(model_type='fake'))
self.assertEqual(labels, FakeLabelData.labels)
def test_fetch_target_label(self):
label = messagebus.handle(
commands.FetchLabels(model_type='fake', label_id=2))[0]
self.assertEqual(label, FakeLabelData.labels[2])
