1

我目前正在使用 Microsoft Azure Emotion API 来查看某些图像的情绪。尽管示例代码有效（Python 2.7），但我希望这不仅仅是一张图片。

我将有一个目录 (URL)，其中包含 100 个图像，标记为 image1、image2、image3。

我正在寻找的是代码的更改，以便为它循环的图像提供平均评分/分数。

我的代码是：

import httplib, urllib, base64

headers = {
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': 'MY KEY HERE',
}

params = urllib.urlencode({
})

body = "{ 'url': 'https://assets.mubi.com/images/notebook/post_images/22267/images-w1400.jpg?1474980339' }"

try:
    conn = httplib.HTTPSConnection('westus.api.cognitive.microsoft.com')
    conn.request("POST", "/emotion/v1.0/recognize?%s" % params, body, headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

我在想一个while循环：

for x in range (0,100):

并将 URL: 更改为带有 (x) 的路径，但我无法使其正常工作。任何帮助将非常感激。

谢谢，内森。

4

1 回答 1

0

正如我在评论中提到的，我假设您想要获取 100 张图像的 facerectangle 和得分平均值。根据我的经验，我们无法直接通过 Emotion API 获得您想要的结果。

我建议您使用循环调用 API 来汇总结果，然后计算平均结果。

你可以参考下面我已经测试成功的代码。

import httplib, urllib, base64, json

headers = {
    # Request headers. Replace the placeholder key below with your subscription key.
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': 'YOUR KEY',
}

params = urllib.urlencode({
})

widthTotal = 0
topTotal = 0
leftTotal = 0
heightTotal = 0
sadnessTotal = 0
neutralTotal = 0
contemptTotal = 0
disgustTotal = 0
angerTotal = 0
surpriseTotal = 0
fearTotal = 0
happinessTotal = 0

count = 100

try:
    for x in range(0, count):
        # Replace the example URL below with the URL of the image you want to analyze.
        body = "{ 'url': 'https://assets.mubi.com/images/notebook/post_images/22267/images-w1400.jpg?1474980339' }"

        # NOTE: You must use the same region in your REST call as you used to obtain your subscription keys.
        #   For example, if you obtained your subscription keys from westcentralus, replace "westus" in the
        #   URL below with "westcentralus".
        conn = httplib.HTTPSConnection('westus.api.cognitive.microsoft.com')
        conn.request("POST", "/emotion/v1.0/recognize?%s" % params, body, headers)
        response = conn.getresponse()
        data = response.read()
        # print(data)

        Arr = json.loads(data, encoding='utf-8')
        # print Arr[0].values()[0]
        # print Arr[0].values()[1]
        # print Arr[0].values()[0]["width"]
        widthTotal += Arr[0].values()[0]["width"]
        topTotal += Arr[0].values()[0]["top"]
        leftTotal += Arr[0].values()[0]["height"]
        heightTotal += Arr[0].values()[0]["height"]
        sadnessTotal += Arr[0].values()[1]["sadness"]
        neutralTotal += Arr[0].values()[1]["neutral"]
        contemptTotal += Arr[0].values()[1]["contempt"]
        disgustTotal += Arr[0].values()[1]["disgust"]
        angerTotal += Arr[0].values()[1]["anger"]
        surpriseTotal += Arr[0].values()[1]["surprise"]
        fearTotal += Arr[0].values()[1]["fear"]
        happinessTotal += Arr[0].values()[1]["happiness"]

        conn.close()

except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

print "width avg: " + str(widthTotal / count)
print "top avg: " + str(topTotal / count)
print "left avg: " + str(leftTotal / count)
print "heigh avg: " + str(heightTotal / count)
print "sadness avg: " + str(sadnessTotal / count)
print "neutral avg: " + str(neutralTotal / count)
print "contempt avg: " + str(contemptTotal / count)
print "disgust avg: " + str(disgustTotal / count)
print "anger avg: " + str(angerTotal / count)
print "surprise avg: " + str(surpriseTotal / count)
print "fear avg: " + str(fearTotal / count)
print "happiness avg: " + str(happinessTotal / count)

打印输出：

在此处输入图像描述

希望它可以帮助你。

于 2017-11-08T07:03:10.677 回答