mirror of https://github.com/vladmandic/automatic
52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
import warnings
|
|
from typing import Union
|
|
import cv2
|
|
import numpy as np
|
|
from PIL import Image
|
|
from modules.control.util import HWC3, resize_image
|
|
|
|
|
|
class MediapipeFaceDetector:
|
|
def __call__(self,
|
|
input_image: Union[np.ndarray, Image.Image] = None,
|
|
max_faces: int = 1,
|
|
min_confidence: float = 0.5,
|
|
output_type: str = "pil",
|
|
detect_resolution: int = 512,
|
|
image_resolution: int = 512,
|
|
**kwargs):
|
|
|
|
from .mediapipe_face_util import generate_annotation
|
|
if "image" in kwargs:
|
|
warnings.warn("image is deprecated, please use `input_image=...` instead.", DeprecationWarning)
|
|
input_image = kwargs.pop("image")
|
|
if input_image is None:
|
|
raise ValueError("input_image must be defined.")
|
|
|
|
if "return_pil" in kwargs:
|
|
warnings.warn("return_pil is deprecated. Use output_type instead.", DeprecationWarning)
|
|
output_type = "pil" if kwargs["return_pil"] else "np"
|
|
if type(output_type) is bool:
|
|
warnings.warn("Passing `True` or `False` to `output_type` is deprecated and will raise an error in future versions")
|
|
if output_type:
|
|
output_type = "pil"
|
|
|
|
if not isinstance(input_image, np.ndarray):
|
|
input_image = np.array(input_image, dtype=np.uint8)
|
|
|
|
input_image = HWC3(input_image)
|
|
input_image = resize_image(input_image, detect_resolution)
|
|
|
|
detected_map = generate_annotation(input_image, max_faces, min_confidence)
|
|
detected_map = HWC3(detected_map)
|
|
|
|
img = resize_image(input_image, image_resolution)
|
|
H, W, _C = img.shape
|
|
|
|
detected_map = cv2.resize(detected_map, (W, H), interpolation=cv2.INTER_LINEAR)
|
|
|
|
if output_type == "pil":
|
|
detected_map = Image.fromarray(detected_map)
|
|
|
|
return detected_map
|