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Running
on
L40S
File size: 1,874 Bytes
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import cv2
import mediapipe as mp
mp_face_mesh = mp.solutions.face_mesh
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_face_detection = mp.solutions.face_detection
def face_rect(images):
with mp_face_detection.FaceDetection(
model_selection=1, min_detection_confidence=0.5
) as face_detection:
for image_cv2 in images:
# Convert the BGR image to RGB and process it with MediaPipe Face Detection.
results = face_detection.process(cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB))
# Draw face detections of each face.
if not results.detections:
yield None
for detection in results.detections:
yield _get_bounding_rect(image_cv2, detection)
def _get_bounding_rect(
image: mp_drawing.np.ndarray,
detection: mp_drawing.detection_pb2.Detection,
):
"""
Stolen from mediapipe.solutions.drawing_utils.draw_detection()
"""
if not detection.location_data:
return
if image.shape[2] != mp_drawing._BGR_CHANNELS:
raise ValueError("Input image must contain three channel bgr data.")
image_rows, image_cols, _ = image.shape
location = detection.location_data
# get bounding box if exists.
if not location.HasField("relative_bounding_box"):
return
relative_bounding_box = location.relative_bounding_box
rect_start_point = mp_drawing._normalized_to_pixel_coordinates(
relative_bounding_box.xmin, relative_bounding_box.ymin, image_cols, image_rows
)
rect_end_point = mp_drawing._normalized_to_pixel_coordinates(
relative_bounding_box.xmin + relative_bounding_box.width,
relative_bounding_box.ymin + relative_bounding_box.height,
image_cols,
image_rows,
)
return *rect_start_point, *rect_end_point
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