解析识别get_face_search结果 [英] Parsing rekognition get_face_search results
问题描述
我正在尝试从get_face_search（）AWS Rekognition API的结果中解析出人脸匹配项。它输出一个Persons数组，该数组中是给定人物和时间戳的另一个FaceMatches数组。我想从FaceMatches数组中获取信息，并能够遍历Face Matchs数组。
I am trying to parse out Face Matches from the results of the get_face_search() AWS Rekognition API. It outputs an array of Persons, within that array is another array of FaceMatches for a given person and timestamp. I want to take information from the FaceMatches array and be able to loop through the array of Face Matches.
我以前对单个数组做过类似的操作，并成功地循环了，但是在这里我可能缺少一些琐碎的事情。
I have done something similar before for single arrays and looped successfully, but I am missing something trivial here perhaps.
此处从API输出：
Response:
{
"JobStatus": "SUCCEEDED",
"NextToken": "U5EdbZ+86xseDBfDlQ2u8QhSVzbdodDOmX/gSbwIgeO90l2BKWvJEscjUDmA6GFDCSSfpKA4",
"VideoMetadata": {
"Codec": "h264",
"DurationMillis": 6761,
"Format": "QuickTime / MOV",
"FrameRate": 30.022184371948242,
"FrameHeight": 568,
"FrameWidth": 320
},
"Persons": [
{
"Timestamp": 0,
"Person": {
"Index": 0,
"BoundingBox": {
"Width": 0.987500011920929,
"Height": 0.7764084339141846,
"Left": 0.0031250000465661287,
"Top": 0.2042253464460373
},
"Face": {
"BoundingBox": {
"Width": 0.6778846383094788,
"Height": 0.3819068372249603,
"Left": 0.10096154361963272,
"Top": 0.2654387652873993
},
"Landmarks": [
{
"Type": "eyeLeft",
"X": 0.33232420682907104,
"Y": 0.4194057583808899
},
{
"Type": "eyeRight",
"X": 0.5422032475471497,
"Y": 0.41616082191467285
},
{
"Type": "nose",
"X": 0.45633792877197266,
"Y": 0.4843473732471466
},
{
"Type": "mouthLeft",
"X": 0.37002310156822205,
"Y": 0.567118763923645
},
{
"Type": "mouthRight",
"X": 0.5330674052238464,
"Y": 0.5631639361381531
}
],
"Pose": {
"Roll": -2.2475271224975586,
"Yaw": 4.371307373046875,
"Pitch": 6.83940315246582
},
"Quality": {
"Brightness": 40.40004348754883,
"Sharpness": 99.95819854736328
},
"Confidence": 99.87971496582031
}
},
"FaceMatches": [
{
"Similarity": 99.81229400634766,
"Face": {
"FaceId": "4699a1eb-9f6e-415d-8716-eef141d23433a",
"BoundingBox": {
"Width": 0.6262923432480737,
"Height": 0.46972032423490747,
"Left": 0.130435005324523403604,
"Top": 0.13354002343240603
},
"ImageId": "1ac790eb-615a-111f-44aa-4017c3c315ad",
"Confidence": 99.19400024414062
}
}
]
},
{
"Timestamp": 66,
"Person": {
"Index": 0,
"BoundingBox": {
"Width": 0.981249988079071,
"Height": 0.7764084339141846,
"Left": 0.0062500000931322575,
"Top": 0.2042253464460373
}
}
},
{
"Timestamp": 133,
"Person": {
"Index": 0,
"BoundingBox": {
"Width": 0.9781249761581421,
"Height": 0.783450722694397,
"Left": 0.0062500000931322575,
"Top": 0.19894365966320038
}
}
},
{
"Timestamp": 199,
"Person": {
"Index": 0,
"BoundingBox": {
"Width": 0.981249988079071,
"Height": 0.783450722694397,
"Left": 0.0031250000465661287,
"Top": 0.19894365966320038
},
"Face": {
"BoundingBox": {
"Width": 0.6706730723381042,
"Height": 0.3778440058231354,
"Left": 0.10817307233810425,
"Top": 0.26679307222366333
},
"Landmarks": [
{
"Type": "eyeLeft",
"X": 0.33244985342025757,
"Y": 0.41591548919677734
},
{
"Type": "eyeRight",
"X": 0.5446155667304993,
"Y": 0.41204410791397095
},
{
"Type": "nose",
"X": 0.4586191177368164,
"Y": 0.479543000459671
},
{
"Type": "mouthLeft",
"X": 0.37614554166793823,
"Y": 0.5639738440513611
},
{
"Type": "mouthRight",
"X": 0.5334802865982056,
"Y": 0.5592300891876221
}
],
"Pose": {
"Roll": -2.4899401664733887,
"Yaw": 3.7596628665924072,
"Pitch": 6.3544135093688965
},
"Quality": {
"Brightness": 40.46360778808594,
"Sharpness": 99.95819854736328
},
"Confidence": 99.89802551269531
}
},
"FaceMatches": [
{
"Similarity": 99.80543518066406,
"Face": {
"FaceId": "4699a1eb-9f6e-415d-8716-eef141d9223a",
"BoundingBox": {
"Width": 0.626294234234737,
"Height": 0.469234234890747,
"Left": 0.130435002334234604,
"Top": 0.13354023423449180603
},
"ImageId": "1ac790eb-615a-111f-44aa-4017c3c315ad",
"Confidence": 99.19400024414062
}
}
]
},
{
"Timestamp": 266,
"Person": {
"Index": 0,
"BoundingBox": {
"Width": 0.984375,
"Height": 0.7852112650871277,
"Left": 0,
"Top": 0.19718310236930847
}
}
}
],
我使用以下方法隔离了时间戳记（只是测试了我的方法）：
I have isolated the timestamps (just testing my approach) using the following:
timestamps = [m['Timestamp'] for m in response['Persons']]
Output is this, as expected - [0, 66, 133, 199, 266]
但是，当我使用FaceMatches尝试相同的操作时，
However, when I try the same thing with FaceMatches, I get an error.
[0, 66, 133, 199, 266]
list indices must be integers or slices, not str: TypeError
Traceback (most recent call last):
File "/var/task/lambda_function.py", line 40, in lambda_handler
matches = [m['FaceMatches']['Face']['FaceId'] for m in response['Persons']]
File "/var/task/lambda_function.py", line 40, in <listcomp>
matches = [m['FaceMatches']['Face']['FaceId'] for m in response['Persons']]
TypeError: list indices must be integers or slices, not str
我最终需要做的是匹配的每张脸：
What I need to end up with is for each face that is matched:
Timestamp
FaceID
Similarity
有人可以帮我一下吗？
推荐答案
根据您的需要，您有两个FaceMatch对象在您的响应中，您可以通过以下方式提取所需的信息：
According to your needs , you have two FaceMatch objects in your response and you can extract required info in this way :
import json
with open('newtest.json') as f:
data = json.load(f)
length =len(data['Persons'])
for i in range(0,length):
try:
print(data['Persons'][i]['FaceMatches'][0]['Similarity'])
print(data['Persons'][i]['FaceMatches'][0]['Face']['FaceId'])
print(data['Persons'][i]['Timestamp'])
except:
continue
我在 data 变量中使用了您的json对象，但我忽略了时间戳，其中没有相应的面部匹配，如果您希望可以提取，则可以用相同的方式
I have taken your json object in data variable and i have ignored timestamps where there is no corresponding facematch, if you wish you can extract then the same way
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