https://github.com/altunenes/handface
A deep learning model for detecting hand-face interactions
https://github.com/altunenes/handface
face facedetection hand handdetection pytorch
Last synced: 26 days ago
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A deep learning model for detecting hand-face interactions
- Host: GitHub
- URL: https://github.com/altunenes/handface
- Owner: altunenes
- License: mit
- Created: 2021-08-03T17:05:21.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2021-08-31T09:07:47.000Z (almost 5 years ago)
- Last Synced: 2026-01-26T16:14:37.388Z (4 months ago)
- Topics: face, facedetection, hand, handdetection, pytorch
- Language: Python
- Homepage:
- Size: 35.2 KB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
[](https://www.codefactor.io/repository/github/emportent/handface)
# HandFace
Deep learning model for detection hand-face interactions
Note: This is a pilot model for a future research project, so it's not finished yet.
The model has been trained in google-collab with 1796 unique images. For now, the total number of classes is 3: Cheek, forehead, and chin. In the labeling process sometimes it was very overwhelming since the human hands were big enough to cover the whole face. So in this scenario, I made my decision based on the place where the hand exerts the most pressure on the face (this paradigm is also consistent with my research )
Update: The train set has been increased to 12.752 after the augmentation process. The model is still in training.
```
=================================================================
Layer (type:depth-idx) Param #
=================================================================
├─Model: 1-1 --
| └─Sequential: 2-1 --
| | └─Focus: 3-1 (5,232)
| | └─Conv: 3-2 (41,568)
| | └─C3: 3-3 (64,896)
| | └─Conv: 3-4 (166,080)
| | └─C3: 3-5 (628,224)
| | └─Conv: 3-6 (663,936)
| | └─C3: 3-7 (2,509,824)
| | └─Conv: 3-8 (2,654,976)
| | └─SPP: 3-9 (1,475,712)
| | └─C3: 3-10 (4,131,840)
| | └─Conv: 3-11 (295,296)
| | └─Upsample: 3-12 --
| | └─Concat: 3-13 --
| | └─C3: 3-14 (1,181,184)
| | └─Conv: 3-15 (73,920)
| | └─Upsample: 3-16 --
| | └─Concat: 3-17 --
| | └─C3: 3-18 (295,680)
| | └─Conv: 3-19 (331,968)
| | └─Concat: 3-20 --
| | └─C3: 3-21 (1,033,728)
| | └─Conv: 3-22 (1,327,488)
| | └─Concat: 3-23 --
| | └─C3: 3-24 (4,131,840)
| | └─Detect: 3-25 (92,943)
=================================================================
Total params: 21,106,335
Trainable params: 0
Non-trainable params: 21,106,335
=================================================================
=================================================================
Layer (type:depth-idx) Param #
=================================================================
├─Model: 1-1 --
| └─Sequential: 2-1 --
| | └─Focus: 3-1 (5,232)
| | └─Conv: 3-2 (41,568)
| | └─C3: 3-3 (64,896)
| | └─Conv: 3-4 (166,080)
| | └─C3: 3-5 (628,224)
| | └─Conv: 3-6 (663,936)
| | └─C3: 3-7 (2,509,824)
| | └─Conv: 3-8 (2,654,976)
| | └─SPP: 3-9 (1,475,712)
| | └─C3: 3-10 (4,131,840)
| | └─Conv: 3-11 (295,296)
| | └─Upsample: 3-12 --
| | └─Concat: 3-13 --
| | └─C3: 3-14 (1,181,184)
| | └─Conv: 3-15 (73,920)
| | └─Upsample: 3-16 --
| | └─Concat: 3-17 --
| | └─C3: 3-18 (295,680)
| | └─Conv: 3-19 (331,968)
| | └─Concat: 3-20 --
| | └─C3: 3-21 (1,033,728)
| | └─Conv: 3-22 (1,327,488)
| | └─Concat: 3-23 --
| | └─C3: 3-24 (4,131,840)
| | └─Detect: 3-25 (92,943)
=================================================================
Total params: 21,106,335
Trainable params: 0
Non-trainable params: 21,106,335
=================================================================
```