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# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
DESCRIPTION:
This sample demonstrates how to generate a human-readable sentence that describes the content
of the image file sample.jpg, using a synchronous client.
By default the caption may contain gender terms such as "man", "woman", or "boy", "girl".
You have the option to request gender-neutral terms such as "person" or "child" by setting
`gender_neutral_caption = True` when calling `analyze`, as shown in this example.
The synchronous (blocking) `analyze` method call returns an `ImageAnalysisResult` object.
Its `caption` property (a `CaptionResult` object) contains:
- The text of the caption. Captions are only supported in English at the moment.
- A confidence score in the range [0, 1], with higher values indicating greater confidences in
the caption.
USAGE:
python sample_caption_image_file.py
Set these two environment variables before running the sample:
1) VISION_ENDPOINT - Your endpoint URL, in the form https://your-resource-name.cognitiveservices.azure.com
where `your-resource-name` is your unique Azure Computer Vision resource name.
2) VISION_KEY - Your Computer Vision key (a 32-character Hexadecimal number)
"""
def sample_caption_image_file():
# [START create_client]
import os
from azure.ai.vision.imageanalysis import ImageAnalysisClient
from azure.ai.vision.imageanalysis.models import VisualFeatures
from azure.core.credentials import AzureKeyCredential
# Set the values of your computer vision endpoint and computer vision key
# as environment variables:
try:
endpoint = os.environ["VISION_ENDPOINT"]
key = os.environ["VISION_KEY"]
except KeyError:
print("Missing environment variable 'VISION_ENDPOINT' or 'VISION_KEY'")
print("Set them before running this sample.")
exit()
# Create an Image Analysis client for synchronous operations,
# using API key authentication
client = ImageAnalysisClient(
endpoint=endpoint,
credential=AzureKeyCredential(key)
)
# [END create_client]
# [START caption]
# Load image to analyze into a 'bytes' object
with open("sample.jpg", "rb") as f:
image_data = f.read()
# Get a caption for the image. This will be a synchronously (blocking) call.
result = client.analyze(
image_data=image_data,
visual_features=[VisualFeatures.CAPTION],
gender_neutral_caption=True, # Optional (default is False)
)
# Print caption results to the console
print("Image analysis results:")
print(" Caption:")
if result.caption is not None:
print(f" '{result.caption.text}', Confidence {result.caption.confidence:.4f}")
# [END caption]
print(f" Image height: {result.metadata.height}")
print(f" Image width: {result.metadata.width}")
print(f" Model version: {result.model_version}")
if __name__ == "__main__":
sample_caption_image_file()
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