---
layout: page
title: Features
permalink: /features/
---
+ **Face Unit Concept**: Similar to controlNet, the program introduces the concept of a face unit. You can configure up to 10 units (3 units are the default setting) in the program settings (sd).
+ **Vladmantic and a1111 Support**
+ **Batch Processing**
+ **Inpainting**: supports "only masked" and mask inpainting.
+ **Performance Improvements**: The overall performance of the software has been enhanced.
+ **FaceSwapLab Tab** providing various tools.
+ **FaceSwapLab Settings**: FaceSwapLab settings are now part of the sd settings. To access them, navigate to the sd settings section.
+ **Face Reuse Via Checkpoints**: The FaceTools tab now allows creating checkpoints, which facilitate face reuse. When a checkpoint is used, it takes precedence over the reference image, and the reference source image is discarded.
+ **Gender Detection**: The program can now detect gender based on faces.
+ **Face Combination (Blending)**: Multiple versions of a face can be combined to enhance the swapping result. This blending happens during checkpoint creation.
+ **Preserve Original Images**: You can opt to keep original images before the swapping process.
+ **Multiple Face Versions for Replacement**: The program allows the use of multiple versions of the same face for replacement.
+ **Face Similarity and Filtering**: You can compare faces against the reference and/or source images.
+ **Face Comparison**: face comparison feature.
+ **Face Extraction**: face extraction with or without upscaling.
+ **Improved Post-Processing**: codeformer, gfpgan, upscaling.
+ **Post Inpainting**: This feature allows the application of image-to-image inpainting specifically to faces.
+ **Upscaled Inswapper**: The program now includes an upscaled inswapper option, which improves results by incorporating upsampling, sharpness adjustment, and color correction before face is merged to the original image.
+ **API with typing support** :
```python
import base64
import io
import requests
from PIL import Image
from client_utils import FaceSwapRequest, FaceSwapUnit, PostProcessingOptions, FaceSwapResponse, pil_to_base64
address = 'http:/127.0.0.1:7860'
# First face unit :
unit1 = FaceSwapUnit(
source_img=pil_to_base64("../../references/man.png"), # The face you want to use
faces_index=(0,) # Replace first face
)
# Second face unit :
unit2 = FaceSwapUnit(
source_img=pil_to_base64("../../references/woman.png"), # The face you want to use
same_gender=True,
faces_index=(0,) # Replace first woman since same gender is on
)
# Post-processing config :
pp = PostProcessingOptions(
face_restorer_name="CodeFormer",
codeformer_weight=0.5,
restorer_visibility= 1)
# Prepare the request
request = FaceSwapRequest (
image = pil_to_base64("test_image.png"),
units= [unit1, unit2],
postprocessing=pp
)
result = requests.post(url=f'{address}/faceswaplab/swap_face', data=request.json(), headers={"Content-Type": "application/json; charset=utf-8"})
response = FaceSwapResponse.parse_obj(result.json())
for img, info in zip(response.pil_images, response.infos):
img.show(title = info)
```