Classification¶
-
class
ClassificationPrediction
(confidence, label)¶ A single prediction from
Classification
.- Parameters
confidence (
float
) – The confidence of this prediction.label (
str
) – The label describing this prediction result.
-
property
label
¶ The label describing this prediction result.
- Return type
str
-
property
confidence
¶ The confidence of this prediction.
- Return type
float
-
class
ClassificationResults
(predictions, duration, image)¶ All the results of classification from
Classification
.Predictions are stored in sorted order, with descending order of confidence.
- Parameters
predictions (
List
[ClassificationPrediction
]) – The list of predictions ordered by confidence descending.duration (
float
) – The duration of the inference.image (
ndarray
) – The image that the inference was performed on.
-
property
duration
¶ The duration of the inference in seconds.
- Return type
float
-
property
predictions
¶ The list of predictions.
- Return type
List
[ClassificationPrediction
]
-
property
image
¶ The image the results were processed on.
- Return type
ndarray
-
class
Classification
(model_id, model_config=None)¶ Identify the most prominent object in an image.
Typical usage:
classifier = edgeiq.Classification('alwaysai/googlenet') classifier.load(engine=edgeiq.Engine.DNN) <get image> results = classifier.classify_image(image) for prediction in results.predictions: print('Label: {}, confidence: {}'.format( prediction.label, prediction.confidence))
- Parameters
model_id (
str
) – The ID of the model you want to use for image classification.
-
classify_image
(image, confidence_level=0.3)¶ Identify the most prominent object in the specified image.
- Parameters
image (
ndarray
) – The image to analyze.confidence_level (
float
) – The minimum confidence level required to successfully accept a classification. Expected range: [0.0, 1.0].
- Return type
-
publish_analytics
(results, tag=None, **kwargs)¶ Publish Classification results to the alwaysAI Analytics Service
- Parameters
results (
ClassificationResults
) – The results to publish.tag – Additional information to assist in querying and visualizations.
- Raises
ConnectionBlockedError
when using connection to the alwaysAI Device Agent and resources are at capacity,- Raises
PacketRateError
when publish rate exceeds current limit,- Raises
PacketSizeError
when packet size exceeds current limit. Packet publish size and rate limits will be provided in the error message.
-
property
accelerator
¶ The accelerator being used.
- Return type
Optional
[Accelerator
]
-
property
colors
¶ The auto-generated colors for the loaded model.
Note: Initialized to None when the model doesn’t have any labels. Note: To update, the new colors list must be same length as the label list.
- Return type
Optional
[ndarray
]
-
property
labels
¶ The labels for the loaded model.
Note: Initialized to None when the model doesn’t have any labels.
- Return type
Optional
[List
[str
]]
-
load
(engine=<Engine.DNN: 'DNN'>, accelerator=<Accelerator.DEFAULT: 'DEFAULT'>)¶ Load the model to an engine and accelerator.
- Parameters
engine (
Engine
) – The engine to load the model toaccelerator (
Accelerator
) – The accelerator to load the model to
-
property
model_config
¶ The configuration of the model that was loaded
- Return type
ModelConfig
-
property
model_id
¶ The ID of the loaded model.
- Return type
str
-
property
model_purpose
¶ The purpose of the model being used.
- Return type
str