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|
import json
from moto.core.common_types import TYPE_RESPONSE
from moto.core.responses import BaseResponse
from .models import RekognitionBackend, rekognition_backends
class RekognitionResponse(BaseResponse):
"""Handler for Rekognition requests and responses."""
def __init__(self) -> None:
super().__init__(service_name="rekognition")
@property
def rekognition_backend(self) -> RekognitionBackend:
return rekognition_backends[self.current_account][self.region]
def get_face_search(self) -> str:
(
job_status,
status_message,
video_metadata,
persons,
next_token,
text_model_version,
) = self.rekognition_backend.get_face_search()
return json.dumps(
{
"JobStatus": job_status,
"StatusMessage": status_message,
"VideoMetadata": video_metadata,
"Persons": persons,
"NextToken": next_token,
"TextModelVersion": text_model_version,
}
)
def get_text_detection(self) -> str:
(
job_status,
status_message,
video_metadata,
text_detections,
next_token,
text_model_version,
) = self.rekognition_backend.get_text_detection()
return json.dumps(
{
"JobStatus": job_status,
"StatusMessage": status_message,
"VideoMetadata": video_metadata,
"TextDetections": text_detections,
"NextToken": next_token,
"TextModelVersion": text_model_version,
}
)
def compare_faces(self) -> str:
(
face_matches,
source_image_orientation_correction,
target_image_orientation_correction,
unmatched_faces,
source_image_face,
) = self.rekognition_backend.compare_faces()
return json.dumps(
{
"FaceMatches": face_matches,
"SourceImageOrientationCorrection": source_image_orientation_correction,
"TargetImageOrientationCorrection": target_image_orientation_correction,
"UnmatchedFaces": unmatched_faces,
"SourceImageFace": source_image_face,
}
)
def detect_labels(self) -> str:
(
labels,
image_properties,
label_model_version,
) = self.rekognition_backend.detect_labels()
return json.dumps(
{
"Labels": labels,
"ImageProperties": image_properties,
"LabelModelVersion": label_model_version,
}
)
def detect_text(self) -> str:
(
text_detections,
text_model_version,
) = self.rekognition_backend.detect_text()
return json.dumps(
{
"TextDetections": text_detections,
"TextModelVersion": text_model_version,
}
)
def detect_custom_labels(self) -> str:
(custom_labels,) = self.rekognition_backend.detect_custom_labels()
return json.dumps(
{
"CustomLabels": custom_labels,
}
)
def start_face_search(self) -> TYPE_RESPONSE:
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) -> TYPE_RESPONSE:
headers = {"Content-Type": "application/x-amz-json-1.1"}
job_id = self.rekognition_backend.start_text_detection()
response = ('{"JobId":"' + job_id + '"}').encode()
return 200, headers, response
|
