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Extends Rekognition support to include get_face_search and start_face_search. (#5115)

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CoderDonohoe 2022-05-10 23:02:21 +01:00 committed by GitHub
parent ac03044c96
commit ae6b28b5b9
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133
moto/rekognition/models.py
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@ -19,9 +19,25 @@ class RekognitionBackend(BaseBackend):
self.__dict__ = {}
self.__init__(region_name)
def start_face_search(self):
return self._job_id()
def start_text_detection(self):
return self._job_id()
def get_face_search(self):
"""
This returns hardcoded values and none of the parameters are taken into account.
"""
return (
self._job_status(),
self._status_message(),
self._video_metadata(),
self._persons(),
self._next_token(),
self._text_model_version(),
)
def get_text_detection(self):
"""
This returns hardcoded values and none of the parameters are taken into account.
@ -65,6 +81,123 @@ class RekognitionBackend(BaseBackend):
"ColorRange": "LIMITED",
}
def _persons(self):
return [
{
"Timestamp": 0,
"Person": {
"Index": 0,
"Face": {
"BoundingBox": {
"Width": 0.42217350006103516,
"Height": 0.9352386593818665,
"Left": 0.31870967149734497,
"Top": -0.0049947104416787624,
},
"Landmarks": [
{
"Type": "eyeLeft",
"X": 0.4800040125846863,
"Y": 0.23425640165805817,
},
{
"Type": "eyeRight",
"X": 0.63795405626297,
"Y": 0.19219470024108887,
},
{
"Type": "mouthLeft",
"X": 0.5283276438713074,
"Y": 0.6190487146377563,
},
{
"Type": "mouthRight",
"X": 0.660395085811615,
"Y": 0.5830448269844055,
},
{
"Type": "nose",
"X": 0.619724690914154,
"Y": 0.3800361752510071,
},
],
"Pose": {
"Roll": -5.063229084014893,
"Yaw": 18.038856506347656,
"Pitch": 12.567241668701172,
},
"Quality": {
"Brightness": 83.42264556884766,
"Sharpness": 67.22731018066406,
},
"Confidence": 99.99860382080078,
},
},
"FaceMatches": [
{
"Similarity": 99.99994659423828,
"Face": {
"FaceId": "f2489050-020e-4c14-8693-63339847a59d",
"BoundingBox": {
"Width": 0.7136539816856384,
"Height": 0.9471719861030579,
"Left": 0.19036999344825745,
"Top": -0.012074699625372887,
},
"ImageId": "f3b180d3-f5ad-39c1-b825-ba30b170a90d",
"ExternalImageId": "Dave_Bloggs",
"Confidence": 99.99970245361328,
},
},
{
"Similarity": 99.9986572265625,
"Face": {
"FaceId": "f0d22a6a-3436-4d23-ae5b-c5cb2e795581",
"BoundingBox": {
"Width": 0.7198730111122131,
"Height": 1.003640055656433,
"Left": 0.1844159960746765,
"Top": -0.00142729002982378,
},
"ImageId": "738d14f3-26be-3066-b1a9-7f4f6bb3ffc6",
"ExternalImageId": "Dave_Bloggs",
"Confidence": 99.99939727783203,
},
},
{
"Similarity": 99.99791717529297,
"Face": {
"FaceId": "c48162bd-a16a-4e04-ad3c-967761895295",
"BoundingBox": {
"Width": 0.7364680171012878,
"Height": 1.0104399919509888,
"Left": 0.1361449956893921,
"Top": -0.009593159891664982,
},
"ImageId": "eae3565c-741b-342c-8e73-379a09ae5346",
"ExternalImageId": "Dave_Bloggs",
"Confidence": 99.99949645996094,
},
},
{
"Similarity": 99.37212371826172,
"Face": {
"FaceId": "651314bb-28d4-405d-9b13-c32e9ff28299",
"BoundingBox": {
"Width": 0.3711090087890625,
"Height": 0.3609749972820282,
"Left": 0.2571589946746826,
"Top": 0.21493400633335114,
},
"ImageId": "068700f5-0b2e-39c0-874b-2c58fa10d833",
"ExternalImageId": "Dave_Bloggs",
"Confidence": 99.99300384521484,
},
},
],
}
]
def _text_detections(self):
return [
{

28
moto/rekognition/responses.py
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@ -13,6 +13,27 @@ class RekognitionResponse(BaseResponse):
"""Return backend instance specific for this region."""
return rekognition_backends[self.region]
def get_face_search(self):
(
job_status,
status_message,
video_metadata,
persons,
next_token,
text_model_version,
) = self.rekognition_backend.get_face_search()
return json.dumps(
dict(
JobStatus=job_status,
StatusMessage=status_message,
VideoMetadata=video_metadata,
Persons=persons,
NextToken=next_token,
TextModelVersion=text_model_version,
)
)
def get_text_detection(self):
(
job_status,
@ -34,6 +55,13 @@ class RekognitionResponse(BaseResponse):
)
)
def start_face_search(self):
headers = {"Content-Type": "application/x-amz-json-1.1"}
job_id = self.rekognition_backend.start_face_search()
response = ('{"JobId":"' + job_id + '"}').encode()
return 200, headers, response
def start_text_detection(self):
headers = {"Content-Type": "application/x-amz-json-1.1"}
job_id = self.rekognition_backend.start_text_detection()

35
tests/test_rekognition/test_rekognition.py
View File

@ -11,6 +11,24 @@ from moto import mock_rekognition
# http://docs.getmoto.org/en/latest/docs/contributing/development_tips/tests.html
@mock_rekognition
def test_start_face_search():
client = boto3.client("rekognition", region_name="ap-southeast-1")
collection_id = "collection_id"
video = {
"S3Object": {
"Bucket": "bucket",
"Name": "key",
}
}
resp = client.start_face_search(CollectionId=collection_id, Video=video)
resp["ResponseMetadata"]["HTTPStatusCode"].should.equal(200)
resp.should.have.key("JobId")
@mock_rekognition
def test_start_text_detection():
client = boto3.client("rekognition", region_name="ap-southeast-1")
@ -28,6 +46,23 @@ def test_start_text_detection():
resp.should.have.key("JobId")
@mock_rekognition
def test_get_face_search():
client = boto3.client("rekognition", region_name="us-east-2")
job_id = "".join(
random.choice(string.ascii_uppercase + string.digits) for _ in range(64)
)
resp = client.get_face_search(JobId=job_id)
resp["ResponseMetadata"]["HTTPStatusCode"].should.equal(200)
resp["JobStatus"].should.equal("SUCCEEDED")
resp["Persons"][0]["FaceMatches"][0]["Face"]["ExternalImageId"].should.equal(
"Dave_Bloggs"
)
@mock_rekognition
def test_get_text_detection():
client = boto3.client("rekognition", region_name="us-east-2")