fix: predict image samples params (#150)

Author: dizcology

.sample_configs/param_handlers/predict_image_classification_sample.py

@@ -32,8 +32,8 @@ def make_instances(filename: str) -> typing.Sequence[google.protobuf.struct_pb2.
 def make_parameters() -> google.protobuf.struct_pb2.Value:
  # See gs://google-cloud-aiplatform/schema/predict/params/image_classification_1.0.0.yaml for the format of the parameters.
  parameters_dict = {
- "confidence_threshold": 0.5,
- "max_predictions": 5
+ "confidenceThreshold": 0.5,
+ "maxPredictions": 5
  }
  parameters = to_protobuf_value(parameters_dict)
 

.sample_configs/param_handlers/predict_image_object_detection_sample.py

@@ -32,8 +32,8 @@ def make_instances(filename: str) -> typing.Sequence[google.protobuf.struct_pb2.
 def make_parameters() -> google.protobuf.struct_pb2.Value:
  # See gs://google-cloud-aiplatform/schema/predict/params/image_object_detection_1.0.0.yaml for the format of the parameters.
  parameters_dict = {
- "confidence_threshold": 0.5,
- "max_predictions": 5
+ "confidenceThreshold": 0.5,
+ "maxPredictions": 5
  }
  parameters = to_protobuf_value(parameters_dict)
 

samples/snippets/predict_image_classification_sample.py

@@ -16,7 +16,8 @@
 import base64
 
 from google.cloud import aiplatform
-from google.cloud.aiplatform.schema import predict
+from google.protobuf import json_format
+from google.protobuf.struct_pb2 import Value
 
 
 def predict_image_classification_sample(
@@ -36,29 +37,25 @@ def predict_image_classification_sample(
 
  # The format of each instance should conform to the deployed model's prediction input schema.
  encoded_content = base64.b64encode(file_content).decode("utf-8")
+ instance_dict = {"content": encoded_content}
 
- instance_obj = predict.instance.ImageClassificationPredictionInstance(
- content=encoded_content)
-
- instance_val = instance_obj.to_value()
- instances = [instance_val]
-
- params_obj = predict.params.ImageClassificationPredictionParams(
- confidence_threshold=0.5, max_predictions=5)
-
+ instance = json_format.ParseDict(instance_dict, Value())
+ instances = [instance]
+ # See gs://google-cloud-aiplatform/schema/predict/params/image_classification_1.0.0.yaml for the format of the parameters.
+ parameters_dict = {"confidenceThreshold": 0.5, "maxPredictions": 5}
+ parameters = json_format.ParseDict(parameters_dict, Value())
  endpoint = client.endpoint_path(
  project=project, location=location, endpoint=endpoint_id
  )
  response = client.predict(
- endpoint=endpoint, instances=instances, parameters=params_obj
+ endpoint=endpoint, instances=instances, parameters=parameters
  )
  print("response")
- print("\tdeployed_model_id:", response.deployed_model_id)
+ print(" deployed_model_id:", response.deployed_model_id)
  # See gs://google-cloud-aiplatform/schema/predict/prediction/classification.yaml for the format of the predictions.
  predictions = response.predictions
- for prediction_ in predictions:
- prediction_obj = predict.prediction.ClassificationPredictionResult.from_map(prediction_)
- print(prediction_obj)
+ for prediction in predictions:
+ print(" prediction:", dict(prediction))
 
 
 # [END aiplatform_predict_image_classification_sample]

samples/snippets/predict_image_object_detection_sample.py

@@ -42,7 +42,7 @@ def predict_image_object_detection_sample(
  instance = json_format.ParseDict(instance_dict, Value())
  instances = [instance]
  # See gs://google-cloud-aiplatform/schema/predict/params/image_object_detection_1.0.0.yaml for the format of the parameters.
- parameters_dict = {"confidence_threshold": 0.5, "max_predictions": 5}
+ parameters_dict = {"confidenceThreshold": 0.5, "maxPredictions": 5}
  parameters = json_format.ParseDict(parameters_dict, Value())
  endpoint = client.endpoint_path(
  project=project, location=location, endpoint=endpoint_id