API
If you're looking for an API, you can choose from your desired programming language.
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import requests
import base64
# Use this function to convert an image file from the filesystem to base64
def image_file_to_base64(image_path):
with open(image_path, 'rb') as f:
image_data = f.read()
return base64.b64encode(image_data).decode('utf-8')
# Use this function to fetch an image from a URL and convert it to base64
def image_url_to_base64(image_url):
response = requests.get(image_url)
image_data = response.content
return base64.b64encode(image_data).decode('utf-8')
# Use this function to convert a list of image URLs to base64
def image_urls_to_base64(image_urls):
return [image_url_to_base64(url) for url in image_urls]
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/faceswap-v3-multifaceswap"
# Request payload
data = {
"source_img": image_url_to_base64("https://segmind-resources.s3.amazonaws.com/output/8ba04e7c-1041-4009-85be-76c8874e1d30-faceswap-v3-multifaceswap-input.jpg"), # Or use image_file_to_base64("IMAGE_PATH")
"target_img": image_url_to_base64("https://segmind-resources.s3.amazonaws.com/output/3b87e9fb-1d51-42ad-ae1e-1ddbcbd6f0d0-front-view-smiley-young-friends-hugging_23-2148342123.jpg"), # Or use image_file_to_base64("IMAGE_PATH")
"input_faces_index": "0,1,2",
"source_faces_index": "0,1,2",
"face_restore": "disable",
"interpolation": "Bilinear",
"detection_face_order": "left-right",
"facedetection": "retinaface_resnet50",
"detect_gender_input": "no",
"detect_gender_source": "no",
"face_restore_weight": 0.75,
"image_format": "jpeg",
"image_quality": 95,
"base64": False
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated imageAttributes
URL for your face image. Use high-resolution close-up shots for best results.
URL of face to swap with. Choose a well-lit image for clarity.
Select index of detected input face. Use '0' for default, '0,1,2' for multiple.
min : 0,
max : 5
Select index of source face. '0' for first, '0,1' for multiple selections.
min : 0,
max : 5
Select face restore model. use 'disable' while swapping multiple faces at once
Allowed values:
Choose interpolation method. 'Bilinear' for most scenarios, 'Lanczos' for detailed.
Allowed values:
Face detection order. Use 'large-small' for prominence, 'top-bottom' for order.
Allowed values:
Select face detection model. 'Retinaface_resnet50' for accuracy, 'YOLOv5n' for speed.
Allowed values:
Detect gender of target face. 'No' by default, specify 'female' or 'male'.
Allowed values:
Detect gender of input face. Use 'no' or specify 'female'/'male'.
Allowed values:
Adjust face restore weight. '0.75' for balance, higher for smoothness.
min : 0,
max : 1
Choose output image format. 'JPEG' for most use, 'PNG' for transparency.
Allowed values:
Set output image quality. '95' for high detail, reduce to save space.
min : 10,
max : 100
Toggle base64 encoding of output. 'False' for direct download, enable for embedding.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
Face Swap V3 Multifaceswap
FaceSwap V3 Multifaceswap model is our latest additon offering seamless face-swapping capabilities, enriched with customizable features to achieve flawless image transformations. Key enhancements over Face Sawp V2 include resolved pixelation issues with face booster models, new face detection order customization, powerful face detection models, and optional gender detection for accurate representation. Whether you're working on a creative project, media production, or social media content, FaceSwap V3 is your ultimate tool for high-quality face swapping.
Key Features of Face Swap V3 Multifaceswap
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Input and Source Faces Index: Specify the index of faces you wish to swap. This feature supports multiple face selection, enabling complex edits and creative modifications.
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Advanced Face Restore Models: Select from cutting-edge model versions like codeformer-v0.1.0.pth to enhance image clarity and realism, ensuring a professional finish.
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Interpolation Techniques: Choose between Bilinear and Nearest interpolation methods for improved face blending, resulting in smoother transitions and natural-looking output.
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Face Detection Ordering: Customize the detection order from large to small faces, allowing you to prioritize key facial features and achieve more effective results.
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High-Precision Face Detection Models: Utilize powerful models, such as retinaface_resnet50, for accurate face localization, ensuring every detail is captured and swapped perfectly.
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Gender Detection: Toggle gender detection settings for both input and target faces. This feature helps tailor the swap, ensuring gender-specific attributes are accurately represented.
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Adjustable Face Restore Weight: Fine-tune the restoration intensity on a scale of 0 to 1, with a default setting of 0.75. This allows for control over how much restoration is applied to the final image.
Use cases
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Creative and Design Projects: Perfect for artists looking to innovate with digital imagery and photo manipulation.
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Entertainment and Media Production: Suitable for movies, video games, and other interactive media requiring realistic face transformations.
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Social Media and Content Creation: Empower influencers and creators to produce engaging content with unique and personalised face swaps.
Other Popular Models
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sdxl-controlnet
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faceswap-v2
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training
sdxl1.0-txt2img
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