watson_developer_cloud.visual_recognition_v3 module

The IBM Watson™ Visual Recognition service uses deep learning algorithms to identify scenes, objects, and faces in images you upload to the service. You can create and train a custom classifier to identify subjects that suit your needs.

class VisualRecognitionV3(version, url='https://gateway.watsonplatform.net/visual-recognition/api', iam_apikey=None, iam_access_token=None, iam_url=None)[source]

Bases: watson_developer_cloud.watson_service.WatsonService

The Visual Recognition V3 service.

default_url = 'https://gateway.watsonplatform.net/visual-recognition/api'
classify(images_file=None, accept_language=None, url=None, threshold=None, owners=None, classifier_ids=None, images_file_content_type=None, images_filename=None, **kwargs)[source]

Classify images.

Classify images with built-in or custom classifiers.

Parameters:images_file (file) – An image file (.jpg, .png) or .zip file with images.

Maximum image size is 10 MB. Include no more than 20 images and limit the .zip file to 100 MB. Encode the image and .zip file names in UTF-8 if they contain non-ASCII characters. The service assumes UTF-8 encoding if it encounters non-ASCII characters. You can also include an image with the url parameter. :param str accept_language: The language of the output class names. The full set of languages is supported for the built-in classifier IDs: default, food, and explicit. The class names of custom classifiers are not translated. The response might not be in the specified language when the requested language is not supported or when there is no translation for the class name. :param str url: The URL of an image to analyze. Must be in .jpg, or .png format. The minimum recommended pixel density is 32X32 pixels per inch, and the maximum image size is 10 MB. You can also include images with the images_file parameter. :param float threshold: The minimum score a class must have to be displayed in the response. Set the threshold to 0.0 to ignore the classification score and return all values. :param list[str] owners: The categories of classifiers to apply. Use IBM to classify against the default general classifier, and use me to classify against your custom classifiers. To analyze the image against both classifier categories, set the value to both IBM and me. The built-in default classifier is used if both classifier_ids and owners parameters are empty. The classifier_ids parameter overrides owners, so make sure that classifier_ids is empty. :param list[str] classifier_ids: Which classifiers to apply. Overrides the owners parameter. You can specify both custom and built-in classifier IDs. The built-in default classifier is used if both classifier_ids and owners parameters are empty. The following built-in classifier IDs require no training: - default: Returns classes from thousands of general tags. - food: Enhances specificity and accuracy for images of food items. - explicit: Evaluates whether the image might be pornographic. :param str images_file_content_type: The content type of images_file. :param str images_filename: The filename for images_file. :param dict headers: A dict containing the request headers :return: A DetailedResponse containing the result, headers and HTTP status code. :rtype: DetailedResponse

detect_faces(images_file=None, url=None, images_file_content_type=None, images_filename=None, **kwargs)[source]

Detect faces in images.

Important: On April 2, 2018, the identity information in the response to calls to the Face model was removed. The identity information refers to the name of the person, score, and type_hierarchy knowledge graph. For details about the enhanced Face model, see the [Release notes](https://console.bluemix.net/docs/services/visual-recognition/release-notes.html#2april2018). Analyze and get data about faces in images. Responses can include estimated age and gender. This feature uses a built-in model, so no training is necessary. The Detect faces method does not support general biometric facial recognition. Supported image formats include .gif, .jpg, .png, and .tif. The maximum image size is 10 MB. The minimum recommended pixel density is 32X32 pixels per inch.

Parameters:images_file (file) – An image file (gif, .jpg, .png, .tif.) or .zip file with

images. Limit the .zip file to 100 MB. You can include a maximum of 15 images in a request. Encode the image and .zip file names in UTF-8 if they contain non-ASCII characters. The service assumes UTF-8 encoding if it encounters non-ASCII characters. You can also include an image with the url parameter. :param str url: The URL of an image to analyze. Must be in .gif, .jpg, .png, or .tif format. The minimum recommended pixel density is 32X32 pixels per inch, and the maximum image size is 10 MB. Redirects are followed, so you can use a shortened URL. You can also include images with the images_file parameter. :param str images_file_content_type: The content type of images_file. :param str images_filename: The filename for images_file. :param dict headers: A dict containing the request headers :return: A DetailedResponse containing the result, headers and HTTP status code. :rtype: DetailedResponse

create_classifier(name, negative_examples=None, negative_examples_filename=None, **kwargs)[source]

Create a classifier.

Train a new multi-faceted classifier on the uploaded image data. Create your custom classifier with positive or negative examples. Include at least two sets of examples, either two positive example files or one positive and one negative file. You can upload a maximum of 256 MB per call. Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier and class names). The service assumes UTF-8 encoding if it encounters non-ASCII characters.

Parameters:name (str) – The name of the new classifier. Encode special characters in

UTF-8. :param file negative_examples: A .zip file of images that do not depict the visual subject of any of the classes of the new classifier. Must contain a minimum of 10 images. Encode special characters in the file name in UTF-8. :param str negative_examples_filename: The filename for negative_examples. :param file positive_examples: A .zip file of images that depict the visual subject of a class in the new classifier. You can include more than one positive example file in a call. Specify the parameter name by appending _positive_examples to the class name. For example, goldenretriever_positive_examples creates the class goldenretriever. Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels. The maximum number of images is 10,000 images or 100 MB per .zip file. Encode special characters in the file name in UTF-8. :param str positive_examples_filename: The filename for positive_examples. :param dict headers: A dict containing the request headers :return: A DetailedResponse containing the result, headers and HTTP status code. :rtype: DetailedResponse

delete_classifier(classifier_id, **kwargs)[source]

Delete a classifier.

Parameters:
  • classifier_id (str) – The ID of the classifier.
  • headers (dict) – A dict containing the request headers
Returns:

A DetailedResponse containing the result, headers and HTTP status code.
Return type:

DetailedResponse
get_classifier(classifier_id, **kwargs)[source]

Retrieve classifier details.

Retrieve information about a custom classifier.

Parameters:
  • classifier_id (str) – The ID of the classifier.
  • headers (dict) – A dict containing the request headers
Returns:

A DetailedResponse containing the result, headers and HTTP status code.
Return type:

DetailedResponse
list_classifiers(verbose=None, **kwargs)[source]

Retrieve a list of classifiers.

Parameters:verbose (bool) – Specify true to return details about the classifiers. Omit

this parameter to return a brief list of classifiers. :param dict headers: A dict containing the request headers :return: A DetailedResponse containing the result, headers and HTTP status code. :rtype: DetailedResponse

update_classifier(classifier_id, negative_examples=None, negative_examples_filename=None, **kwargs)[source]

Update a classifier.

Update a custom classifier by adding new positive or negative classes (examples) or by adding new images to existing classes. You must supply at least one set of positive or negative examples. For details, see [Updating custom classifiers](https://console.bluemix.net/docs/services/visual-recognition/customizing.html#updating-custom-classifiers). Encode all names in UTF-8 if they contain non-ASCII characters (.zip and image file names, and classifier and class names). The service assumes UTF-8 encoding if it encounters non-ASCII characters. Tip: Don’t make retraining calls on a classifier until the status is ready. When you submit retraining requests in parallel, the last request overwrites the previous requests. The retrained property shows the last time the classifier retraining finished.

Parameters:
  • classifier_id (str) – The ID of the classifier.
  • negative_examples (file) – A .zip file of images that do not depict the visual

subject of any of the classes of the new classifier. Must contain a minimum of 10 images. Encode special characters in the file name in UTF-8. :param str negative_examples_filename: The filename for negative_examples. :param file positive_examples: A .zip file of images that depict the visual subject of a class in the classifier. The positive examples create or update classes in the classifier. You can include more than one positive example file in a call. Specify the parameter name by appending _positive_examples to the class name. For example, goldenretriever_positive_examples creates the class goldenretriever. Include at least 10 images in .jpg or .png format. The minimum recommended image resolution is 32X32 pixels. The maximum number of images is 10,000 images or 100 MB per .zip file. Encode special characters in the file name in UTF-8. :param str positive_examples_filename: The filename for positive_examples. :param dict headers: A dict containing the request headers :return: A DetailedResponse containing the result, headers and HTTP status code. :rtype: DetailedResponse

get_core_ml_model(classifier_id, **kwargs)[source]

Retrieve a Core ML model of a classifier.

Download a Core ML model file (.mlmodel) of a custom classifier that returns <tt>”core_ml_enabled”: true</tt> in the classifier details.

Parameters:
  • classifier_id (str) – The ID of the classifier.
  • headers (dict) – A dict containing the request headers
Returns:

A DetailedResponse containing the result, headers and HTTP status code.
Return type:

DetailedResponse
delete_user_data(customer_id, **kwargs)[source]

Delete labeled data.

Deletes all data associated with a specified customer ID. The method has no effect if no data is associated with the customer ID. You associate a customer ID with data by passing the X-Watson-Metadata header with a request that passes data. For more information about personal data and customer IDs, see [Information security](https://console.bluemix.net/docs/services/visual-recognition/information-security.html).

Parameters:
  • customer_id (str) – The customer ID for which all data is to be deleted.
  • headers (dict) – A dict containing the request headers
Returns:

A DetailedResponse containing the result, headers and HTTP status code.
Return type:

DetailedResponse
class Class(class_name)[source]

Bases: object

A category within a classifier.

Attr str class_name:
 The name of the class.
class ClassResult(class_name, score, type_hierarchy)[source]

Bases: object

Result of a class within a classifier.

Attr str class_name:
 Name of the class.
Attr float score:
 Confidence score for the property in the range of 0 to 1. A higher

score indicates greater likelihood that the class is depicted in the image. The default threshold for returning scores from a classifier is 0.5. :attr str type_hierarchy: Knowledge graph of the property. For example, /fruit/pome/apple/eating apple/Granny Smith. Included only if identified.

class ClassifiedImage(classifiers, source_url=None, resolved_url=None, image=None, error=None)[source]

Bases: object

Results for one image.

Attr str source_url:
 (optional) Source of the image before any redirects. Not

returned when the image is uploaded. :attr str resolved_url: (optional) Fully resolved URL of the image after redirects are followed. Not returned when the image is uploaded. :attr str image: (optional) Relative path of the image file if uploaded directly. Not returned when the image is passed by URL. :attr ErrorInfo error: (optional) Information about what might have caused a failure, such as an image that is too large. Not returned when there is no error. :attr list[ClassifierResult] classifiers: The classifiers.

class ClassifiedImages(custom_classes, images_processed, images, warnings=None)[source]

Bases: object

Results for all images.

Attr int custom_classes:
 Number of custom classes identified in the images.
Attr int images_processed:
 Number of images processed for the API call.
Attr list[ClassifiedImage] images:
 Classified images.
Attr list[WarningInfo] warnings:
 (optional) Information about what might cause less

than optimal output. For example, a request sent with a corrupt .zip file and a list of image URLs will still complete, but does not return the expected output. Not returned when there is no warning.

class Classifier(classifier_id, name, owner=None, status=None, core_ml_enabled=None, explanation=None, created=None, classes=None, retrained=None, updated=None)[source]

Bases: object

Information about a classifier.

Attr str classifier_id:
 ID of a classifier identified in the image.
Attr str name:Name of the classifier.
Attr str owner:(optional) Unique ID of the account who owns the classifier. Returned

when verbose=`true`. Might not be returned by some requests. :attr str status: (optional) Training status of classifier. :attr bool core_ml_enabled: (optional) Whether the classifier can be downloaded as a Core ML model after the training status is ready. :attr str explanation: (optional) If classifier training has failed, this field might explain why. :attr datetime created: (optional) Date and time in Coordinated Universal Time (UTC) that the classifier was created. :attr list[Class] classes: (optional) Classes that define a classifier. :attr datetime retrained: (optional) Date and time in Coordinated Universal Time (UTC) that the classifier was updated. Returned when verbose=`true`. Might not be returned by some requests. Identical to updated and retained for backward compatibility. :attr datetime updated: (optional) Date and time in Coordinated Universal Time (UTC) that the classifier was most recently updated. The field matches either retrained or created. Returned when verbose=`true`. Might not be returned by some requests.

class ClassifierResult(name, classifier_id, classes)[source]

Bases: object

Classifier and score combination.

Attr str name:Name of the classifier.
Attr str classifier_id:
 ID of a classifier identified in the image.
Attr list[ClassResult] classes:
 Classes within the classifier.
class Classifiers(classifiers)[source]

Bases: object

A container for the list of classifiers.

Attr list[Classifier] classifiers:
 List of classifiers.
class DetectedFaces(images_processed, images, warnings=None)[source]

Bases: object

Results for all faces.

Attr int images_processed:
 Number of images processed for the API call.
Attr list[ImageWithFaces] images:
 The images.
Attr list[WarningInfo] warnings:
 (optional) Information about what might cause less

than optimal output. For example, a request sent with a corrupt .zip file and a list of image URLs will still complete, but does not return the expected output. Not returned when there is no warning.

class ErrorInfo(code, description, error_id)[source]

Bases: object

Information about what might have caused a failure, such as an image that is too large. Not returned when there is no error.

Attr int code:HTTP status code.
Attr str description:
 Human-readable error description. For example, `File size limit

exceeded`. :attr str error_id: Codified error string. For example, limit_exceeded.

class Face(age=None, gender=None, face_location=None)[source]

Bases: object

Information about the face.

Attr FaceAge age:
 (optional) Age information about a face.
Attr FaceGender gender:
 (optional) Information about the gender of the face.
Attr FaceLocation face_location:
 (optional) The location of the bounding box around

the face.

class FaceAge(score, min=None, max=None)[source]

Bases: object

Age information about a face.

Attr int min:(optional) Estimated minimum age.
Attr int max:(optional) Estimated maximum age.
Attr float score:
 Confidence score in the range of 0 to 1. A higher score indicates

greater confidence in the estimated value for the property.

class FaceGender(gender, score)[source]

Bases: object

Information about the gender of the face.

Attr str gender:
 Gender identified by the face. For example, MALE or FEMALE.
Attr float score:
 Confidence score in the range of 0 to 1. A higher score indicates

greater confidence in the estimated value for the property.

class FaceLocation(width, height, left, top)[source]

Bases: object

The location of the bounding box around the face.

Attr float width:
 Width in pixels of face region.
Attr float height:
 Height in pixels of face region.
Attr float left:
 X-position of top-left pixel of face region.
Attr float top:Y-position of top-left pixel of face region.
class ImageWithFaces(faces, image=None, source_url=None, resolved_url=None, error=None)[source]

Bases: object

Information about faces in the image.

Attr list[Face] faces:
 Faces detected in the images.
Attr str image:(optional) Relative path of the image file if uploaded directly. Not

returned when the image is passed by URL. :attr str source_url: (optional) Source of the image before any redirects. Not returned when the image is uploaded. :attr str resolved_url: (optional) Fully resolved URL of the image after redirects are followed. Not returned when the image is uploaded. :attr ErrorInfo error: (optional) Information about what might have caused a failure, such as an image that is too large. Not returned when there is no error.

class WarningInfo(warning_id, description)[source]

Bases: object

Information about something that went wrong.

Attr str warning_id:
 Codified warning string, such as limit_reached.
Attr str description:
 Information about the error.