ComfyUI-Deepface

ComfyUI-Deepface
★ 36

人脸识别人脸属性分析身份验证ComfyUI节点
将DeepFace人脸分析库封装为ComfyUI节点，便于在可视化流程中进行人脸检测、识别与属性分析，简化集成与调用。
💡 在ComfyUI流程中进行人脸识别与属性分析
🍴 7 Forks💻 Python🔄 2026-02-01
📦
网盘下载
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https://pan.quark.cn/s/8f9eee5e2cdb
📦 requirements.txt
deepface==0.0.89
tf_keras
verify workflow
verify with distances workflow
verify with none-handling workflow
📄 README

ComfyUI Deepface

ComfyUI nodes wrapping the deepface library.

Requirements

Install dependencies:

pip install -r requirements.txt

Nodes

Deepface Extract Faces

Given a set of input images, outputs the cropped detected faces from each image. Each image

is resized to the target size. If no face is detected in the image, will output the original image,

resized to the target face size.

  • Inputs:
  • images: The input images to extract faces from.
  • target_face_size: The size (width and height) to resize the extracted faces to. Default is 224.
  • detector_backend: The face detection backend to use. Options include “opencv”, “ssd”, “dlib”, “mtcnn”, “retinaface”, “mediapipe”, “yolov8”, “yunet”, “fastmtcnn”. Default is “retinaface”.
  • enforce_detection: If true, the node will not output anything ((None,)) if no faces are detected. If false, it will output the original image resized to the target size if no face is detected. Default is false.

  • Outputs:
  • face_images batch of cropped face images detected in the input images

    • Deepface Verify

    Given a set of input images and a set of reference (face) images, only output the input images with an average distance

    to the faces in the reference images less than or equal to the specified threshold. Output images are sorted by average

    distance to the reference image faces (nearest first).

    In addition to distance, outputs include the ratio of reference images that each input image was verified to be a

    face match of, according to the default distance threshold of the model selected. This measure complements the average

    distance measure, as there may be one image that is very close (small distance), despite the input image not being a

    great match against all reference images.

    Both inputs accept image batches.

  • Outputs:
  • verified_images images that contain faces below the distance threshold and above the ratio threshold, sorted from smallest distance to largest
  • verified_image_distances numbers of the average distance from the input image face to each reference image face
  • verified_image_verified_ratios the ratio of reference images that deepface marks as “verified” to the total number of reference images
  • rejected_images images that contain faces above (or equal to) the distance threshold or below the ratio threshold, sorted from smallest distance to largest
  • rejected_image_distances numbers of the average distance from the input image face to each reference image face
  • rejected_image_verified_ratios the ratio of reference images that deepface marks as “verified” to the total number of reference images

    • Note that any individual output may be None if there are no input images matching the criteria.

    Nodes from was-node-suite-comfyui and

    pythongosssss can be used to display the output distances:

    ComfyUI’s built-in PreviewImage and SaveImage nodes do not handle empty/None inputs, ComfyUI-Impact-Pack

    provides nodes that can be used to handle empty/None outputs in conjunction with PreviewImage/SaveImage:

    Credits

    Inspired by CeFurkan‘s use of deepface to evaluate finetuning outputs. 🙌