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import cv2
import insightface
from insightface.app import FaceAnalysis
import os
class FaceSwapper:
def __init__(self):
self.app = FaceAnalysis(name='buffalo_l')
self.app.prepare(ctx_id=0, det_size=(640, 640))
self.swapper = insightface.model_zoo.get_model(
'inswapper_128.onnx', download=True, download_zip=True
)
def swap_faces(self, source_path, source_face_idx, target_path, target_face_idx):
source_img = cv2.imread(source_path)
target_img = cv2.imread(target_path)
if source_img is None or target_img is None:
raise ValueError("Could not read one or both images")
source_faces = self.app.get(source_img)
target_faces = self.app.get(target_img)
source_faces = sorted(source_faces, key=lambda x: x.bbox[0])
target_faces = sorted(target_faces, key=lambda x: x.bbox[0])
if len(source_faces) < source_face_idx or source_face_idx < 1:
raise ValueError(f"Source image contains {len(source_faces)} faces, but requested face {source_face_idx}")
if len(target_faces) < target_face_idx or target_face_idx < 1:
raise ValueError(f"Target image contains {len(target_faces)} faces, but requested face {target_face_idx}")
source_face = source_faces[source_face_idx - 1]
target_face = target_faces[target_face_idx - 1]
result = self.swapper.get(target_img, target_face, source_face, paste_back=True)
return result
def count_faces(self, img_path):
"""
Counts the number of faces in the given image file.
"""
img = cv2.imread(img_path)
# Use your face detector here. For example, with OpenCV's Haar cascade:
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.1, 4)
return len(faces)
def main():
# Paths relative to root
source_path = os.path.join("SinglePhoto", "data_src.jpg")
target_path = os.path.join("SinglePhoto", "data_dst.jpg")
output_dir = os.path.join("SinglePhoto", "output")
if not os.path.exists(output_dir):
os.makedirs(output_dir)
swapper = FaceSwapper()
try:
# Ask user for target_face_idx, default to 1 if no input or invalid input
try:
user_input = input("Enter the target face index (starting from 1, default is 1): ")
target_face_idx = int(user_input) if user_input.strip() else 1
if target_face_idx < 1:
print("Invalid index. Using default value 1.")
target_face_idx = 1
except ValueError:
print("Invalid input. Using default value 1.")
target_face_idx = 1
try:
result = swapper.swap_faces(
source_path=source_path,
source_face_idx=1,
target_path=target_path,
target_face_idx=target_face_idx
)
except ValueError as ve:
if "Target image contains" in str(ve):
print(f"Target face idx {target_face_idx} not found, trying with idx 1.")
result = swapper.swap_faces(
source_path=source_path,
source_face_idx=1,
target_path=target_path,
target_face_idx=1
)
else:
raise ve
output_path = os.path.join(output_dir, "swapped_face.jpg")
cv2.imwrite(output_path, result)
print(f"Face swap completed successfully. Result saved to: {output_path}")
except Exception as e:
print(f"Error occurred: {str(e)}")
if __name__ == "__main__":
main() |