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import cv2
import mediapipe as mp
import numpy as np
from rembg import remove
from PIL import Image
import io
class FaceSegmenter:
def __init__(self, threshold=0.5):
self.threshold = threshold
self.face_detection = mp.solutions.face_detection.FaceDetection(
model_selection=1, min_detection_confidence=0.5
)
self.selfie_segmentation = mp.solutions.selfie_segmentation.SelfieSegmentation(
model_selection=1
)
def segment_face(self, image_input):
# Handle both file paths and numpy arrays
if isinstance(image_input, str):
# Load from file path
image = cv2.imread(image_input)
if image is None:
raise ValueError("Image not found or unable to load.")
elif isinstance(image_input, np.ndarray):
# Use numpy array directly (BGR format)
image = image_input.copy()
else:
raise ValueError("Input must be file path string or numpy array")
rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
face_results = self.face_detection.process(rgb_image)
if not face_results.detections:
# Use rembg with numpy array input
pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
output_image = remove(pil_image) # rembg handles PIL Images
# Convert to numpy array and remove alpha channel
output_image = np.array(output_image)
if output_image.shape[2] == 4:
output_image = cv2.cvtColor(output_image, cv2.COLOR_RGBA2RGB)
return output_image
# Existing face segmentation logic
detection = face_results.detections[0]
bboxC = detection.location_data.relative_bounding_box
h, w, _ = image.shape
x, y, width, height = (
int(bboxC.xmin * w), int(bboxC.ymin * h),
int(bboxC.width * w), int(bboxC.height * h)
)
segmentation_results = self.selfie_segmentation.process(rgb_image)
mask = (segmentation_results.segmentation_mask > self.threshold).astype(np.uint8)
face_mask = np.zeros_like(mask)
face_mask[y:y+height, x:x+width] = mask[y:y+height, x:x+width]
segmented_face = cv2.bitwise_and(image, image, mask=face_mask)
return segmented_face
# Updated helper methods to handle numpy arrays
def save_segmented_face(self, image_input, output_path):
segmented_face = self.segment_face(image_input)
cv2.imwrite(output_path, segmented_face)
def show_segmented_face(self, image_input):
segmented_face = self.segment_face(image_input)
cv2.imshow("Segmented Face", segmented_face)
cv2.waitKey(0)
cv2.destroyAllWindows() |