This is the face keypoint train code of project face-detection-project

Related tags

Deep Learningface-key-point-pytorch
Overview

face-key-point-pytorch

Python Python torch

1. Data structure

The structure of landmarks_jpg is like below:

|--landmarks_jpg
|----AFW
|------AFW_134212_1_0.jpg
|------AFW_134212_1_1.jpg
|----HELEN
|-------HELEN_232194_1_0.jpg
|-------HELEN_232194_1_1.jpg
|----IBUG
|------IBUG_image_003_1_0.jpg
|------IBUG_image_003_1_1.jpg
|----LFPW
|------LFPW_image_test_0001_0.jpg
|------LFPW_image_test_0001_1.jpg

The structure of landmarks_label is like below:

|--landmarks_label
|----AFW
|------AFW_134212_1_0_pts
|------AFW_134212_1_1_pts
|----HELEN
|-------HELEN_232194_1_0_pts
|-------HELEN_232194_1_1_pts
|----IBUG
|------IBUG_image_003_1_0_pts
|------IBUG_image_003_1_1_pts
|----LFPW
|------LFPW_image_test_0001_0_pts
|------LFPW_image_test_0001_1_pts

You can download it by yourself. You can also download the data from the cloud drive:

name link
landmarks_jpg.zip https://pan.baidu.com/s/1AJKpa0ac-6ZPWBASiMv87Q code: nujr
landmarks_label.zip https://pan.baidu.com/s/1wBAZMFkNQS6R6KLkRl6ktw code: zgl0

2. how to train

First, install the third-party package:

pip install -r requirements.txt

Then just simply run the below command:

python3 train.py

if you want to use the pretrained models, you can revise the below code as you need:

load_pretrain_model = False
model_dir=r".\pretrain_models\face-keypoint-vgg16-0.pth"
if load_pretrain_model:
    checkpoint = torch.load(model_dir)
    net.load_state_dict(checkpoint)

3. how to test

Revise the test file name in predict.py and then run the below command:

python3 predict.py
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