def __init__(self):
# Configure API key authorization: Apikey
configuration = cloudmersive_image_api_client.Configuration()
configuration.api_key['Apikey'] = CLOUDMERSIVE_API_KEY
# Create an instance of the API class
self.api_instance = cloudmersive_image_api_client.RecognizeApi(
cloudmersive_image_api_client.ApiClient(configuration))
def match_image(check_image, target_image):
# Configure API key authorization: Apikey
configuration = cloudmersive_image_api_client.Configuration()
#'YOUR_API_KEY'
configuration.api_key['Apikey'] = apikey
# create an instance of the API class
api_instance = cloudmersive_image_api_client.FaceApi(cloudmersive_image_api_client.ApiClient(configuration))
try:
# Compare and match faces
api_response = api_instance.face_compare(check_image, target_image)
except ApiException as e:
#describe the error
print("Exception when calling FaceApi->face_compare: %s\n" % e)
return api_response
def match_image(check_image, target_image):
"""Connect to the cloudmersive host in order to ask to perform the match
using the 2 image given as parameter. check_image is the image that will
be machted with target_image.
:param path: The path of the two images
:type path: string
:return: the Json containing infos about the match
:rtype: Json
"""
# Configure API key authorization: Apikey
configuration = cloudmersive_image_api_client.Configuration()
configuration.api_key['Apikey'] = apikey
# create an instance of the API class
instance = cloudmersive_image_api_client.ApiClient(configuration)
api_instance = cloudmersive_image_api_client.FaceApi(instance)
try:
# Compare and match faces
api_response = api_instance.face_compare(check_image, target_image)
except ApiException as e:
# Describe the error
print("Exception when calling FaceApi->face_compare: %s\n" % e)
return api_response
def predict_image_to_caption(cloudmersive_api_key):
# Configure API key authorization: Apikey
configuration = cloudmersive_image_api_client.Configuration()
configuration.api_key['Apikey'] = cloudmersive_api_key
# create an instance of the API class
api_instance = cloudmersive_image_api_client.RecognizeApi(cloudmersive_image_api_client.ApiClient(configuration))
image_file = "website-image.jpg"
prediction = ""
try:
# Describe an image in natural language
api_response = api_instance.recognize_describe(image_file)
prediction = "Please listen to our prediction of your webpage. "
if api_response.highconfidence == False:
prediction = prediction + api_response.best_outcome.description + ". However, we are not very sure about this prediction."
else:
prediction = api_response.best_outcome.description
except Exception as e:
prediction = "Sorry, an error occured while we were trying to guess the content of the page. Please try again."
return prediction
from __future__ import print_function
import time
import cloudmersive_image_api_client
from cloudmersive_image_api_client.rest import ApiException
from pprint import pprint
# Configure API key authorization: Apikey
configuration = cloudmersive_image_api_client.Configuration()
configuration.api_key['Apikey'] = '7cb7be78-35a6-4a37-98b0-d93098d9ddbb'
# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed
# configuration.api_key_prefix['Apikey'] = 'Bearer'
# create an instance of the API class
api_instance = cloudmersive_image_api_client.RecognizeApi(
cloudmersive_image_api_client.ApiClient(configuration))
image_file = 'hamburguer.jpg'
# file | Image file to perform the operation on. Common file formats such as PNG, JPEG are supported.
try:
# Describe an image in natural language
api_response = api_instance.recognize_describe(image_file)
pprint(api_response)
except ApiException as e:
print("Exception when calling RecognizeApi->recognize_describe: %s\n" % e)