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**用于识别海岸倾斜航空影像中水体的Doodleverse/Segmentation Zoo Res-UNet模型** 本模型数据集基于海岸影像及配套标注构建。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}。 本套文件需配合Segmentation Zoo*使用。每个模型对应三个根文件名一致的文件，分别为： 1. **`.json` 配置文件**：该文件由Segmentation Gym** 用于生成权重文件，其中包含模型构建说明、所用数据集信息，以及模型预测的使用指南。该文件实用性极强，掌握它即可完全通晓整个Doodleverse工具体系。 2. **`.h5` 权重文件**：该文件由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Segmentation Gym** 的`seg_images_in_folder.py` 脚本，或Segmentation Zoo* 的`select_model_and_batch_process_folder.py` 脚本调用，以对指定文件夹内的影像进行语义分割推理。 3. **`_modelcard.json` 模型卡片文件**：该JSON文件包含用于描述模型来源、训练配置及所属训练数据集的各类字段。该文件与前文所述的`config`配置文件存在部分冗余内容，二者均涵盖模型训练与部署的相关说明。程序本身无需调用该文件，但它属于重要的元数据，需与构成模型的其他文件一同留存，因此被纳入模型套件中。 参考文献 * https://github.com/Doodleverse/segmentation_zoo ** https://github.com/Doodleverse/segmentation_gym