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visual_recognition_v3.py
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72 lines (58 loc) · 2.75 KB
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from __future__ import print_function
import json
from os.path import join, dirname
from watson_developer_cloud import VisualRecognitionV3, WatsonApiException
test_url = 'https://www.ibm.com/ibm/ginni/images' \
'/ginni_bio_780x981_v4_03162016.jpg'
visual_recognition = VisualRecognitionV3('2016-05-20', api_key='YOUR API KEY')
# with open(join(dirname(__file__), '../resources/cars.zip'), 'rb') as cars, \
# open(join(dirname(__file__), '../resources/trucks.zip'), 'rb') as
# trucks:
# print(json.dumps(visual_recognition.create_classifier('Cars vs Trucks',
# cars_positive_examples=cars,
#
# negative_examples=trucks), indent=2))
car_path = join(dirname(__file__), '../resources/cars.zip')
with open(car_path, 'rb') as images_file:
parameters = json.dumps({'threshold': 0.1, 'classifier_ids': ['default']})
car_results = visual_recognition.classify(images_file=images_file,
parameters=parameters)
print(json.dumps(car_results, indent=2))
# Example with no deprecated
try:
with open(car_path, 'rb') as images_file:
car_results = visual_recognition.classify(
images_file=images_file,
threshold='0.1',
classifier_ids=['default'])
print(json.dumps(car_results, indent=2))
except WatsonApiException as ex:
print(ex.httpResponse.json())
# print(json.dumps(visual_recognition.get_classifier('YOUR CLASSIFIER ID'),
# indent=2))
# with open(join(dirname(__file__), '../resources/car.jpg'), 'rb') as
# image_file:
# print(json.dumps(visual_recognition.update_classifier(
# 'CarsvsTrucks_1479118188',
#
# cars_positive_examples=image_file), indent=2))
url_result = visual_recognition.classify(parameters=json.dumps({'url': test_url}))
print(json.dumps(url_result, indent=2))
faces_result = visual_recognition.detect_faces(parameters=json.dumps({'url': test_url}))
print(json.dumps(faces_result, indent=2))
# print(json.dumps(visual_recognition.delete_classifier(classifier_id='YOUR
# CLASSIFIER ID'), indent=2))
print(json.dumps(visual_recognition.list_classifiers(), indent=2))
#file_path = join(dirname(__file__), '../resources/text.png')
#with open(file_path, 'rb') as image_file:
# text_results = visual_recognition.recognize_text(images_file=image_file)
# print(json.dumps(text_results, indent=2))
face_path = join(dirname(__file__), '../resources/face.jpg')
with open(face_path, 'rb') as image_file:
face_result = visual_recognition.detect_faces(images_file=image_file)
print(json.dumps(face_result, indent=2))
#Core ml model example
# model_name = '{0}.mlmodel'.format(classifier_id)
# core_ml_model = visual_recognition.get_core_ml_model(classifier_id)
# with open('/tmp/{0}'.format(model_name), 'wb') as fp:
# fp.write(core_ml_model.content)