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A collection of deep learning frameworks ported to Keras for face analysis.
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| 2026-08-04 | 275 |
| 2026-08-06 | 275 |
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# face-toolbox-keras A collection of deep learning frameworks ported to Keras for face detection, face segmentation, face parsing, iris detection, and face verification.  ## Descriptions This repository contains deep learning frameworks that we collected and ported to Keras. We wrapped those models into separate modules that aim to provide their functionality to users within 3 lines of code. - **Face detection:** - S3FD model ported from [1adrianb/face-alignment](https://github.com/1adrianb/face-alignment). - MTCNN model ported from [davidsandberg/facenet](https://github.com/davidsandberg/facenet). - **Face landmarks detection:** - 2DFAN-4, 2DFAN-2, and 2DFAN-1 models ported from [1adrianb/face-alignment](https://github.com/1adrianb/face-alignment). - **Face parsing:** - BiSeNet model ported from [zllrunning/face-parsing.PyTorch](https://github.com/zllrunning/face-parsing.PyTorch). - **Eye region landmarks detection:** - ELG model is ported from [swook/GazeML](https://github.com/swook/GazeML). - **Face verification:** - InceptionResNetV1 model (model name: 20180402-114759) ported from [davidsandberg/facenet](https://github.com/davidsandberg/facenet). - LResNet100E-IR model ported from [deepinsight/insightface](https://github.com/deepinsight/insightface). - IR50 model ported from [ZhaoJ9014/face.evoLVe.PyTorch](https://github.com/ZhaoJ9014/face.evoLVe.PyTorch). - **Gender and age estimation:** - MobileNet model ported from [deepinsight/insightface](https://github.com/deepinsight/insightface). ##### *Each module follows the license of their source repo. Notice that some models were trained on dataset with non-commercial license. ## Usage [](https://colab.research.google.com/github/shaoanlu/face-toolbox-keras/blob/master/demo.ipynb) (Please run `pip install keras==2.2.4` before initializaing models.) This colab demo requires a GPU instance. It demonstrates all face analysis functionalities above. ### 1. Face detection ```python models.detector.face_detector.FaceAlignmentDetector(fd_weights_path=..., lmd_weights_path=..., fd_type="s3fd") ``` **Arguments** - `fd_weights_path`: A string. Path to weights file of the face detector model. - `lmd_weights_path`: A string. Path to weights file of the landmarks detector model. - `fd_type`: A string. Face detector backbone model of either `s3fd` or `mtcnn`. **Example** ```python from models.detector import face_detector im = cv2.imread(PATH_TO_IMAGE)[..., ::-1] fd = face_detector.FaceAlignmentDetector() bboxes = fd.detect_face(im, with_landmarks=False) ``` ### 2. Face landmarks detection The default model is 2DFAN-4. Lite models of 2DFAN-1 and 2DFAN-2 are also provided. | GPU | 2DFAN-1 | 2DFAN-2 | 2DFAN-4 | |:---:|:-------:|:-------:|:-------:| | K80 | 74.3ms | 92.2ms | 133ms | **Example** ```python from models.detector import face_detector im = cv2.imread(PATH_TO_IMAGE)[..., ::-1] fd = face_detector.FaceAlignmentDetector() bboxes, landmarks = fd.detect_face(im, with_landmarks=True) ``` ### 3. Face parsing ```python models.parser.face_parser.FaceParser(path_bisenet_weights=...) ``` **Arguments** - `path_bisenet_weights`: A string. Path to weights file of the model. **Example** ```python from models.parser import face_parser im = cv2.imread(PATH_TO_IMAGE)[..., ::-1] fp = face_parser.FaceParser() # fp.set_detector(fd) # fd = face_detector.FaceAlignmentDetector() parsing_map = fp.parse_face(im, bounding_box=None, with_detection=False) ``` ### 4. Eye region landmarks detection ```python models.detector.iris_detector.IrisDetector() ``` Faster face detection using MTCNN can be found in [this](https://github.com/shaoanlu/GazeML-keras) repo. **Example** ```python from models.detector import iris_detector im = cv2.imread(PATH_TO_IMAGE)[..., ::-1] idet = iris_detector.IrisDetector() idet.set_detec
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:656e976cc4aa7a68, llm:Description and README: 'A collection of deep learning frameworks ported to Keras for face detection, face segmentation, face parsing, iris detection, and face verification.' Topics include face-detection, face-landmark-detection, face-parsing, face-segmentation, face-verification, gender-estimation, insightface, iris-detection.
matched fp:656e976cc4aa7a68, llm:Description and README: 'A collection of deep learning frameworks ported to Keras for face detection, face segmentation, face parsing, iris detection, and face verification.' Topics include face-detection, face-landmark-detection, face-parsing, face-segmentation, face-verification, gender-estimation, insightface, iris-detection.
matched fp:656e976cc4aa7a68, llm:Description and README: 'A collection of deep learning frameworks ported to Keras for face detection, face segmentation, face parsing, iris detection, and face verification.' Topics include face-detection, face-landmark-detection, face-parsing, face-segmentation, face-verification, gender-estimation, insightface, iris-detection.