in lab2/inference_client/edge_agent_pb2_grpc.py [0:0]
def DetectAnomalies(self, request, context):
"""Detects anomalies in the supplied image.
The response from DetectAnomalies includes a boolean prediction that
the image contains one or more anomalies and a confidence value for the prediction.
The model that you use with DetectAnomalies must be running.
You can get the current status by calling DescribeModel. To start running
a model, use StartModel.
DetectAnomalies supports packed bitmaps (images) in interleaved RGB888 format.
The minimum supported image dimension is 64x64 pixels. The maximum supported
image dimension is 4096x4096 pixels.
You can send the image in the protobuf message or through a shared memory
segment. Serializing large images into the protobuf message can significantly
increase the latency of calls to DetectAnomalies. For the best latency,
we recommended that you use shared memory.
Status codes:
0. OK - DetectAnomalies successfully made a prediction.
2. UNKNOWN - An unknown error has occurred.
3. INVALID_ARGUMENT - One or more input parameters is invalid. Check the error message for more details.
5. NOT_FOUND - A model with the specified name wasn't found.
8. RESOURCE_EXHAUSTED - There isn't enough resources to perform this operation.
For example, The Lookout for Vision Edge Agent can't keep up with the rate of calls to DetectAnomalies.
Check the error message for more details.
9. FAILED_PRECONDITION - DetectAnomalies was called for model that is
not in the RUNNING state.
13. INTERNAL - An internal error has occurred.
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')