def predictions(self, image):
"""Get detection result for input image.
Parameters
----------
image : `numpy.ndarray`
The input image in [h, n, c] ndarry format.
Returns
-------
list
List of batch prediction resutls.
Each element is a dictionary containing:
{'name', 'score', 'mid', 'bounding_poly'}.
"""
from google.cloud import vision
from google.protobuf.json_format import MessageToJson
from protobuf_to_dict import protobuf_to_dict
image_bytes = ndarray_to_bytes(image)
image = vision.types.Image(content=image_bytes)
response = self.model.object_localization(
image=image).localized_object_annotations
predictions = []
for object in response:
predictions.append(protobuf_to_dict(object))
return predictions
def predictions(self, image):
"""Get prediction for input image
Parameters
----------
image : `numpy.ndarray`
The input image in [h, n, c] ndarry format.
Returns
-------
list
List of anitporn prediction resutls.
Each element is a dictionary containing:
{'class_name', 'probability'}
"""
image_bytes = ndarray_to_bytes(image)
predictions = self.model.antiPorn(image_bytes)
return predictions['result']
def predictions(self, image):
"""Get prediction for input image.
Parameters
----------
image : `numpy.ndarray`
The input image in [h, n, c] ndarry format.
Returns
-------
list
List of prediction resutls.
Each element is a dictionary containing:
{'adult', 'medical', 'racy', 'spoof', 'violence'}.
"""
from google.cloud import vision
from protobuf_to_dict import protobuf_to_dict
image_bytes = ndarray_to_bytes(image)
image = vision.types.Image(content=image_bytes)
response = self.model.safe_search_detection(image=image)
predictions = protobuf_to_dict(response)['safe_search_annotation']
return predictions