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import numpy as np
import cv2 as cv
import mediapipe as mp
from mediapipe.tasks import python
from mediapipe.tasks.python import vision
base_options = python.BaseOptions(model_asset_path='resources/fd_model.tflite')
options = vision.FaceDetectorOptions(base_options=base_options)
detector = vision.FaceDetector.create_from_options(options)
def format_detections(detection_result):
faces = []
for detection in detection_result.detections:
face = {
"bbox": {
"x": detection.bounding_box.origin_x,
"y": detection.bounding_box.origin_y,
"width": detection.bounding_box.width,
"height": detection.bounding_box.height,
},
}
faces.append(face)
return faces
def faces_detection_controller(image: bytes):
cv_image = cv.imdecode(np.frombuffer(image, np.uint8), cv.IMREAD_COLOR)
mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=cv_image)
# Process image
detection_result = detector.detect(mp_image)
return format_detections(detection_result)
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