HRNet v1:Deep High-Resolution Representation Learning for Human Pose Estimation
HRNet v2:High-Resolution Representations for Labeling Pixels and Regions
HRNet v1 源代码 pytorch:https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
HRNet v2 源代码 pytorch:https://github.com/HRNet/HRNet-Semantic-Segmentation
train.ipynb:
模型训练,包含超参设置、模型调用、训练、可视化。test_crop_image.py:
模型测试,包含模型加载、测试、可视化。dataloaders/generater.py:
数据加载,数据路径获取、图片读取、预处理及在线扩充。model/seg_hrnet:
模型定义。utils/loss.py:
损失函数,包含dice_loss、ce_dice_loss、jaccard_loss(IoU loss)、ce_jaccard_loss、tversky_loss、focal_loss
utils/metrics.py:
评价指标,包含precision、recall、accuracy、iou、f1
等。train.html:
训练过程记录,保存为html文件。