It's not clear how to do label detection with google-cloud-vision. There's a complete

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Using the cloud vision api for label detection. about google-cloud-python HOT 1 OPEN

nwaughachukwuma commented on June 13, 2024

Using the cloud vision api for label detection.

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Comments (1)

ohmayr commented on June 13, 2024

Hi @nwaughachukwuma, thanks for reaching out. I tried the sample provided in the link and it seems to work as expected.

Code:

# Imports the Google Cloud client library
from google.cloud import vision



def run_quickstart() -> vision.EntityAnnotation:
    """Provides a quick start example for Cloud Vision."""

    # Instantiates a client
    client = vision.ImageAnnotatorClient()

    # The URI of the image file to annotate
    file_uri = "gs://cloud-samples-data/vision/label/wakeupcat.jpg"

    image = vision.Image()
    image.source.image_uri = file_uri

    # Performs label detection on the image file
    response = client.label_detection(image=image)
    print("response: ", response)
    labels = response.label_annotations

    print("Labels:")
    for label in labels:
        print(label.description)

    return labels

run_quickstart()

Output:

response:  label_annotations {
  mid: "/m/01yrx"
  description: "Cat"
  score: 0.956459463
  topicality: 0.956459463
}
label_annotations {
  mid: "/m/0d4v4"
  description: "Window"
  score: 0.938840091
  topicality: 0.938840091
}
label_annotations {
  mid: "/m/0307l"
  description: "Felidae"
  score: 0.89566052
  topicality: 0.89566052
}
label_annotations {
  mid: "/m/01lrl"
  description: "Carnivore"
  score: 0.885138333
  topicality: 0.885138333
}
label_annotations {
  mid: "/m/01k9lj"
  description: "Jaw"
  score: 0.880326807
  topicality: 0.880326807
}
label_annotations {
  mid: "/m/07k6w8"
  description: "Small to medium-sized cats"
  score: 0.863107383
  topicality: 0.863107383
}
label_annotations {
  mid: "/m/0244x1"
  description: "Gesture"
  score: 0.852604866
  topicality: 0.852604866
}
label_annotations {
  mid: "/m/01l7qd"
  description: "Whiskers"
  score: 0.84995687
  topicality: 0.84995687
}
label_annotations {
  mid: "/m/031b6r"
  description: "Window blind"
  score: 0.834581673
  topicality: 0.834581673
}
label_annotations {
  mid: "/m/0276krm"
  description: "Fawn"
  score: 0.816135049
  topicality: 0.816135049
}

Labels:
Cat
Window
Felidae
Carnivore
Jaw
Small to medium-sized cats
Gesture
Whiskers
Window blind
Fawn

Feel free to reach out if you have any questions related to the Python client. For any API specific questions, kindly submit feedback on this link.

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