def post(self):
'''Make a prediction given input data'''
result = {'status': 'error'}
args = image_parser.parse_args()
image_data = args['image'].read()
image = read_image(image_data)
label_preds = self.model_wrapper.predict(image)
result['predictions'] = label_preds
result['status'] = 'ok'
return result
def post(self):
'''Make a prediction given input data'''
result = {'status': 'error'}
args = image_parser.parse_args()
image_data = args['image'].read()
image = read_image(image_data)
preds = self.model_wrapper.predict(image)
label_preds = [{'label_id': p[0], 'label': p[1], 'probability': p[2]} for p in [x for x in preds]]
result['predictions'] = label_preds
result['status'] = 'ok'
return result
def post(self):
"""Make a prediction given input data"""
result = {'status': 'error'}
args = image_parser.parse_args()
image_data = args['image'].read()
image = read_image(image_data)
resized_im, seg_map = self.model_wrapper.predict(image)
result['image_size'] = resized_im.size
result['seg_map'] = seg_map
result['status'] = 'ok'
return result
def post(self):
"""Make a prediction given input data"""
result = {'status': 'error'}
args = image_parser.parse_args()
image_data = args['image'].read()
try:
image = read_image(image_data)
preds = self.model_wrapper.predict(image)
label_preds = [{'probability': float(preds)}]
result['predictions'] = label_preds
result['status'] = 'ok'
except ValueError as e:
abort(400, str(e))
return result
def post(self):
"""Make a prediction given input data"""
result = {'status': 'error'}
args = input_parser.parse_args()
try:
input_data = args['file'].read()
image = read_image(input_data)
except OSError as e:
abort(400,
"Please submit a valid image in PNG, Tiff or JPEG format")
label_preds = self.model_wrapper.predict(image)
result['predictions'] = label_preds
result['status'] = 'ok'
return result