Doodleverse/Segmentation Zoo Res-UNet models for identifying water in oblique aerial photos of coasts.

<strong>Doodleverse/Segmentation Zoo Res-UNet models for identifying water in oblique aerial photos of coasts.</strong> These model data are based on images of coasts and associated labels. Models have been fitted to the following types of data 1. RGB (3 band): red, green, blue Classes are: {0: water, 1: land}. These files are used in conjunction with Segmentation Zoo* For each model, there are 3 files with the same root name: 1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images 3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model References * https://github.com/Doodleverse/segmentation_zoo ** https://github.com/Doodleverse/segmentation_gym<strong>Doodleverse/分割集（Segmentation Zoo）Res-UNet模型：用于海岸倾斜航空影像中的水体识别</strong> 本模型数据集基于海岸影像及对应标注标签构建。本模型适配以下类型的数据：1. 三波段RGB影像：包含红、绿、蓝三个通道。分类类别为：{0: 水体，1: 陆地}。 上述文件需配合分割集使用。针对每个模型，均包含3个根文件名一致的文件： 1. <strong>'.json' 配置文件：</strong>该文件由分割训练框架（Segmentation Gym）** 生成权重文件时使用，其包含模型构建、所用数据集的相关说明，以及模型推理的使用指南。该文件简洁实用，掌握该文件即可完全掌握整个Doodleverse套件。 2. <strong>'.h5' 权重文件：</strong>该文件由分割训练框架（Segmentation Gym）** 的`train_model.py`脚本生成，存储了训练完成的模型参数权重。可通过分割训练框架的`seg_images_in_folder.py`脚本，或分割集的`select_model_and_batch_process_folder.py`脚本，对指定文件夹内的影像进行语义分割。 3. <strong>'_modelcard.json' 模型卡片文件：</strong>该JSON文件包含若干字段，用于完整描述模型的起源、训练参数及所用数据集。该文件与上文所述的`config`配置文件存在部分冗余内容，二者均包含模型训练与部署的相关说明。尽管程序本身不会调用该模型卡片文件，但它属于重要的元数据，需与构成该模型的其他文件一同留存，因此被纳入模型的组成部分。 参考文献 * https://github.com/Doodleverse/segmentation_zoo ** https://github.com/Doodleverse/segmentation_gym