зеркало из https://github.com/Azure/azcv.git
81 строка
2.2 KiB
Python
81 строка
2.2 KiB
Python
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# -*- coding: utf-8 -*-
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# Author: Graham.Williams@togaware.com
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#
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# A script to detect faces in an image.
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#
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# ml faces azcv <path>
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from msrest.authentication import CognitiveServicesCredentials
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from azure.cognitiveservices.vision.computervision import ComputerVisionClient
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import os
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import argparse
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from textwrap import fill
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from mlhub.pkg import azkey, is_url
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from mlhub.utils import get_cmd_cwd
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# ----------------------------------------------------------------------
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# Parse command line arguments
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# ----------------------------------------------------------------------
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option_parser = argparse.ArgumentParser(add_help=False)
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option_parser.add_argument(
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'path',
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help='path or url to image')
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args = option_parser.parse_args()
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# ----------------------------------------------------------------------
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SERVICE = "Computer Vision"
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KEY_FILE = os.path.join(os.getcwd(), "private.txt")
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# Request subscription key and endpoint from user.
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subscription_key, endpoint = azkey(KEY_FILE, SERVICE, verbose=False)
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# Set credentials.
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credentials = CognitiveServicesCredentials(subscription_key)
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# Create client.
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client = ComputerVisionClient(endpoint, credentials)
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# ----------------------------------------------------------------------
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# URL or path
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# ----------------------------------------------------------------------
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path = args.path
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# Check the URL supplied or path exists and is an image.
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# ----------------------------------------------------------------------
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# Analyze
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# ----------------------------------------------------------------------
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image_features = ["color"]
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# Send provided image (url or path) to azure to analyse.
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if is_url(path):
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analysis = client.analyze_image(path, image_features)
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else:
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path = os.path.join(get_cmd_cwd(), path)
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with open(path, 'rb') as fstream:
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analysis = client.analyze_image_in_stream(fstream, image_features)
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print(f"{not analysis.color.is_bw_img},{analysis.color.accent_color}," +
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f"{analysis.color.dominant_color_background}," +
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f"{analysis.color.dominant_color_foreground},", end='')
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start = ''
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for c in analysis.color.dominant_colors:
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print(start + c, end='')
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start = ' '
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print()
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