"landmarks", local_image)
print("\nLandmarks in the local image:")
if len(local_image_landmarks.result["landmarks"]) == 0:
print("No landmarks detected.")
else:
for landmark in local_image_landmarks.result["landmarks"]:
print(landmark["name"])
# END Detect domain-specific content (celebrities/landmarks) in a local image
# Detect domain-specific content (celebrities/landmarks) in a remote image by:
# 1. Calling the Computer Vision service's analyze_image_by_domain with the:
# - domain-specific content to search for
# - image
# 2. Displaying any domain-specific content (celebrities/landmarks).
remote_image_celebs = computervision_client.analyze_image_by_domain(
"celebrities", remote_image_url)
print("\nCelebrities in the remote image:")
if len(remote_image_celebs.result["celebrities"]) == 0:
print("No celebrities detected.")
else:
for celeb in remote_image_celebs.result["celebrities"]:
print(celeb["name"])
remote_image_landmarks = computervision_client.analyze_image_by_domain(
"landmarks", remote_image_url)
print("\nLandmarks in the remote image:")
if len(remote_image_landmarks.result["landmarks"]) == 0:
print("No landmarks detected.")
else:
display momentarily.
Location: {}""".format(url))
# Type of prediction.
domain = "landmarks"
mlpreview(url)
# English language response.
language = "en"
try:
analysis = client.analyze_image_by_domain(domain, url, language)
except Exception as e:
catch_exception(e, url)
mlask()
for landmark in analysis.result["landmarks"]:
print('\nIdentified "{}" with confidence {}.'.format(
landmark["name"], round(landmark["confidence"], 2)))
mlask(begin="\n", end="\n")
url1 = "https://cdn.britannica.com/"
url2 = "95/94195-050-FCBF777E/"
url3 = "Golden-Gate-Bridge-San-Francisco.jpg"
url = url1 + url2 + url3
print(landmark["name"])
print()
'''
END - Detect Domain-specific Content - local
'''
# <snippet_celebs>
'''
Detect Domain-specific Content - remote
This example detects celebrites and landmarks in remote images.
'''
print("===== Detect Domain-specific Content - remote =====")
# URL of one or more celebrities
remote_image_url_celebs = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/ComputerVision/Images/faces.jpg"
# Call API with content type (celebrities) and URL
detect_domain_results_celebs_remote = computervision_client.analyze_image_by_domain("celebrities", remote_image_url_celebs)
# Print detection results with name
print("Celebrities in the remote image:")
if len(detect_domain_results_celebs_remote.result["celebrities"]) == 0:
print("No celebrities detected.")
else:
for celeb in detect_domain_results_celebs_remote.result["celebrities"]:
print(celeb["name"])
# </snippet_celebs>
# <snippet_landmarks>
# Call API with content type (landmarks) and URL
detect_domain_results_landmarks = computervision_client.analyze_image_by_domain("landmarks", remote_image_url)
print()
client = ComputerVisionClient(uri, credencias)
client.api_version
""""""
from azure.cognitiveservices.vision.computervision.models import VisualFeatureTypes
url = 'https://pbs.twimg.com/media/ECx6hK-WwAAPzeE.jpg'
analise_de_imagem = client.analyze_image(url, visual_features = [VisualFeatureTypes.tags])
for tag in analise_de_imagem.tags:
print(tag)
analise_de_celebridades = client.analyze_image_by_domain("celebrities", url, "en")
for celebridade in analise_de_celebridades.result["celebrities"]:
print(celebridade['name'])
print(celebridade['confidence'])
descricacao = client.describe_image(url,3,"en")
descricacao
for caption in descricacao.captions:
print(caption.text)
print(caption.confidence)
"""# Streaming + Vision API"""
import json
# Collect the Config #
# #
#################################################
with open('config.json') as config_file:
data = json.load(config_file)
KEY = data['key']
ENDPOINT = data['endpoint']
computervision_client = ComputerVisionClient(ENDPOINT,
CognitiveServicesCredentials(KEY))
# Get an image to find its tags
remote_image_url = "https://www.thetimes.co.uk/imageserver/image/methode%2Ftimes%2Fprod%2Fweb%2Fbin%2Fc994ba96-5632-11e9-a8f5-a9ee11ff7e6d.jpg?crop=4896%2C2754%2C0%2C255&resize=1200"
# Alternate 1
remote_image_url = "https://mymodernmet.com/wp/wp-content/uploads/2018/11/egyptian-pyramids-3.jpg"
# Alternate 2
remote_image_url = "https://cdn.galaxy.tf/unit-media/tc-default/uploads/images/poi_photo/001/549/654/golden-gate-bridge-1-standard.jpg"
# Call API with content type (landmarks) and URL
detect_domain_results_landmarks = computervision_client.analyze_image_by_domain(
"landmarks", remote_image_url)
print()
print("Landmarks in the remote image:")
if len(detect_domain_results_landmarks.result["landmarks"]) == 0:
print("No landmarks detected.")
else:
for landmark in detect_domain_results_landmarks.result["landmarks"]:
print(landmark["name"])
img.show()
# Call API to describe image
description_result = computer_vision_client.describe_image(query_image_url)
# Get the captions (descriptions) from the response, with confidence level
print()
print("Description of image: ")
if (len(description_result.captions) == 0):
print("No description detected.")
else:
for caption in description_result.captions:
print("'{}' with confidence {:.2f}%".format(caption.text,
caption.confidence * 100))
print()
# Detect domain-specific content, celebrities, in image
# Call API with content type (celebrities) and URL
detect_domain_celebrity_result = computer_vision_client.analyze_image_by_domain(
"celebrities", query_image_url)
# Print detection results with name
celebrities = detect_domain_celebrity_result.result["celebrities"]
celebrity_name = ''
print("Celebrities in the image:")
if len(detect_domain_celebrity_result.result["celebrities"]) == 0:
print("No celebrities detected.")
else:
for celeb in celebrities:
celebrity_name = celeb["name"]
print(celeb["name"])