How can we access and display the likelihood values for each category in the safe search annotation?
To access and display the likelihood values for each category in the safe search annotation using the Google Vision API's advanced images understanding feature, you can utilize the response received from the API call. The response contains a JSON object that includes the safe search annotation information, including the likelihood values for different categories.
When making a request to the API, you need to specify the image you want to analyze. The API will then process the image and return a response containing various information, including the safe search annotation. The safe search annotation provides an assessment of the likelihood that the image contains explicit content in different categories, such as adult, medical, violent, spoof, and racy.
To access the likelihood values for each category, you can parse the JSON response and extract the relevant information. The safe search annotation is represented by the "safeSearchAnnotation" field in the response. Within this field, you will find the likelihood values for each category.
Here is an example of how you can access and display the likelihood values using Python:
python
import json
# Assuming you have the API response stored in a variable called 'response'
response = {
"safeSearchAnnotation": {
"adult": "VERY_UNLIKELY",
"spoof": "UNLIKELY",
"medical": "VERY_UNLIKELY",
"violence": "VERY_UNLIKELY",
"racy": "VERY_UNLIKELY"
}
}
# Parse the JSON response
data = json.loads(response)
# Access and display the likelihood values
likelihood_values = data["safeSearchAnnotation"]
for category, likelihood in likelihood_values.items():
print(f"{category}: {likelihood}")
The above code will output the likelihood values for each category:
adult: VERY_UNLIKELY spoof: UNLIKELY medical: VERY_UNLIKELY violence: VERY_UNLIKELY racy: VERY_UNLIKELY
By accessing and displaying these likelihood values, you can determine the level of explicit content in the image across different categories. This information can be useful in various applications, such as content moderation, filtering, or parental control systems.
To access and display the likelihood values for each category in the safe search annotation using the Google Vision API's advanced images understanding feature, you need to parse the API response and extract the relevant information from the "safeSearchAnnotation" field. This information can help you assess the presence of explicit content in different categories.
Other recent questions and answers regarding Advanced images understanding:
- What are some predefined categories for object recognition in Google Vision API?
- What is the recommended approach for using the safe search detection feature in combination with other moderation techniques?
- How can we obtain the safe search annotation using the Google Vision API in Python?
- What are the five categories included in the safe search detection feature?
- How does the Google Vision API's safe search feature detect explicit content within images?
- How can we visually identify and highlight the detected objects in an image using the pillow library?
- How can we organize the extracted object information in a tabular format using the pandas data frame?
- How can we extract all the object annotations from the API's response?
- What libraries and programming language are used to demonstrate the functionality of the Google Vision API?
- How does the Google Vision API perform object detection and localization in images?
View more questions and answers in Advanced images understanding