[EISeg] Release EISeg 1.0 (PaddlePaddle#2326)

EISeg/docs/image.md

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+简体中文 | [English](image_en.md)
+
+# 图片标注
+
+以下内容为2D图片标注模型下载及EISeg2D图片标注流程，具体如下：
+
+## 模型准备
+
+在使用EISeg前，请先下载模型参数。EISeg开放了在COCO+LVIS、大规模人像数据、mapping_challenge，Chest X-Ray，MRSpineSeg，LiTS及百度自建质检数据集上训练的7个垂类方向模型，满足通用场景、人像场景、建筑物标注，医疗影像肝脏，胸腔，椎骨及铝板质检的标注需求。其中模型结构对应EISeg交互工具中的网络选择模块，用户需要根据自己的场景需求选择不同的网络结构和加载参数。
+
+
+| 模型类型   | 适用场景                   | 模型结构       | 模型下载地址                                                     |
+| ---------- | -------------------------- | -------------- | ------------------------------------------------------------ |
+| 高精度模型 | 通用场景的图像标注 | HRNet18_OCR64  | [static_hrnet18_ocr64_cocolvis](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18_ocr64_cocolvis.zip) |
+| 轻量化模型 | 通用场景的图像标注 | HRNet18s_OCR48 | [static_hrnet18s_ocr48_cocolvis](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18s_ocr48_cocolvis.zip) |
+| 高精度模型 | 通用图像标注场景      | EdgeFlow | [static_edgeflow_cocolvis](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_edgeflow_cocolvis.zip) |
+| 高精度模型 | 人像标注场景      | HRNet18_OCR64  | [static_hrnet18_ocr64_human](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18_ocr64_human.zip) |
+| 轻量化模型 | 人像标注场景       | HRNet18s_OCR48 | [static_hrnet18s_ocr48_human](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18s_ocr48_human.zip) |
+| 轻量化模型 | 遥感建筑物标注场景    | HRNet18s_OCR48 | [static_hrnet18_ocr48_rsbuilding_instance](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18_ocr48_rsbuilding_instance.zip) |
+| 高精度模型\* | x光胸腔标注场景       | Resnet50_Deeplabv3+ | [static_resnet50_deeplab_chest_xray](https://paddleseg.bj.bcebos.com/eiseg/0.5/static_resnet50_deeplab_chest_xray.zip) |
+| 轻量化模型 | 医疗肝脏标注场景       | HRNet18s_OCR48 | [static_hrnet18s_ocr48_lits](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18s_ocr48_lits.zip) |
+| 轻量化模型\* | MRI椎骨图像标注场景       | HRNet18s_OCR48 | [static_hrnet18s_ocr48_MRSpineSeg](https://paddleseg.bj.bcebos.com/eiseg/0.5/static_hrnet18s_ocr48_MRSpineSeg.zip) |
+| 轻量化模型\* | 质检铝板瑕疵标注场景      | HRNet18s_OCR48 | [static_hrnet18s_ocr48_aluminium](https://paddleseg.bj.bcebos.com/eiseg/0.5/static_hrnet18s_ocr48_aluminium.zip) |
+
+**NOTE**： 将下载的模型结构`*.pdmodel`及相应的模型参数`*.pdiparams`需要放到同一个目录下，加载模型时只需选择`*.pdiparams`结尾的模型参数位置即可， `*.pdmodel`会自动加载。在使用`EdgeFlow`模型时，请将`使用掩膜`关闭，其他模型使用时请勾选`使用掩膜`。其中，`高精度模型`推荐使用带有显卡的电脑，以便获得更流畅的标注体验。
+
+
+## 使用
+
+打开软件后，在对项目进行标注前，需要进行如下设置：
+
+1. **模型参数加载**
+
+   根据标注场景，选择合适的网络模型及参数进行加载。选择合适的模型及参数下载解压后，模型结构`*.pdmodel`及相应的模型参数`*.pdiparams`需要放到同一个目录下，加载模型时只需选择`*.pdiparams`结尾的模型参数位置即可。静态图模型初始化时间稍长，请耐心等待模型加载完成后进行下一步操作。正确加载的模型参数会记录在`近期模型参数`中，可以方便切换，并且下次打开软件时自动加载退出时的模型参数。
+
+2. **图像加载**
+
+   打开图像/图像文件夹。当看到主界面图像正确加载，`数据列表`正确出现图像路径即可。
+
+3. **标签添加/加载**
+
+   添加/加载标签。可以通过`添加标签`新建标签，标签分为4列，分别对应像素值、说明、颜色和删除。新建好的标签可以通过`保存标签列表`保存为txt文件，其他合作者可以通过`加载标签列表`将标签导入。通过加载方式导入的标签，重启软件后会自动加载。
+
+4. **开始标注**
+
+    标注首先进入交互式分割模式。鼠标左键代表正点击，表示所选择的前景部分，鼠标右键代表负点击，为用户选定的背景区域。用户可以通过正负点击操作来选择感兴趣的区域， 直到满意为止。交互完成后使用Space(空格)完成交互标注，此时出现多边形边界，进入多边形标注模式。多边形可以删除，使用鼠标左边可 以对锚点进行拖动，鼠标左键双击锚点可以删 除锚点，双击两点之间的边则可在此边添加一个锚点。
+
+5. **自动保存设置**
+
+   在使用中可以将`自动保存`设置上，设定好文件夹即可，这样在使用时切换图像会自动将完成标注的图像进行保存。
+
+当设置完成后即可开始进行标注，默认情况下常用的按键/快捷键如下，如需修改可按`E`弹出快捷键修改。
+
+| 部分按键/快捷键       | 功能              |
+| --------------------- | ----------------- |
+| 鼠标左键              | 增加正样本点      |
+| 鼠标右键              | 增加负样本点      |
+| 鼠标中键              | 平移图像          |
+| Ctrl+鼠标中键（滚轮） | 缩放图像          |
+| S                     | 切换上一张图      |
+| F                     | 切换下一张图      |
+| Space（空格）         | 完成标注/切换状态 |
+| Ctrl+Z                | 撤销              |
+| Ctrl+Shift+Z          | 清除              |
+| Ctrl+Y                | 重做              |
+| Ctrl+A                | 打开图像          |
+| Shift+A               | 打开文件夹        |
+| E                     | 打开快捷键表      |
+| Backspace（退格）     | 删除多边形        |
+| 鼠标双击（点）        | 删除点            |
+| 鼠标双击（边）        | 添加点            |
+
+## 特色功能使用说明
+
+- **多边形**
+
+    - 交互完成后使用Space（空格）完成交互标注，此时出现多边形边界；
+    - 当需要在多边形内部继续进行交互，则使用空格切换为交互模式，此时多边形无法选中和更改。
+    - 多边形可以删除，使用鼠标左边可以对锚点进行拖动，鼠标左键双击锚点可以删除锚点，双击两点之间的边则可在此边添加一个锚点。
+    - 打开`保留最大连通块`后，所有的点击只会在图像中保留面积最大的区域，其余小区域将不会显示和保存。
+
+- **保存格式**
+
+    - 打开保存`JSON保存`或`COCO保存`后，多边形会被记录，加载时会自动加载。
+    - 若不设置保存路径，默认保存至当前图像文件夹下的label文件夹中。
+    - 如果有图像之间名称相同但后缀名不同，可以打开`标签和图像使用相同扩展名`。
+    - 还可设置灰度保存、伪彩色保存和抠图保存，见工具栏中7-9号工具。
+
+- **生成mask**
+
+    - 标签按住第二列可以进行拖动，最后生成mask时会根据标签列表从上往下进行覆盖。
+
+- **界面模块**
+
+    - 可在`显示`中选择需要显示的界面模块，正常退出时将会记录界面模块的状态和位置，下次打开自动加载。
+
+- **垂类分割**
+
+    EISeg目前已添加对遥感图像和医学影像分割的支持，使用相关功能需要安装额外依赖。
+
+    - 分割遥感图像请安装GDAL，相关安装及介绍具体详见[遥感标注垂类建设](remote_sensing.md)。
+    - 分割医学影像请安装SimpleITK，相关安装及介绍具体详见[医疗标注垂类建设](medical.md)。
+
+- **视频标注及3D医疗图像标注**
+
+    EISeg目前已添加对视频标注和腹腔多器官及ct椎骨数据3D医疗图像标注的支持，使用相关功能需要安装额外依赖。
+
+    - 视频标注及3D医疗图像标注请安装VTK，相关安装及介绍具体详见[视频标注功能](video.md)。
+
+- **脚本工具使用**
+
+    EISeg目前提供包括标注转PaddleX数据集、划分COCO格式以及语义标签转实例标签等脚本工具，相关使用方式详见[脚本工具使用](tools.md)。

EISeg/docs/image_en.md

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+English | [简体中文](image.md)
+# 2D Image Anotation
+
+The following content is about how to use EISeg to annotate 2D images. Model preparation and how to use can be seen as follow:
+
+## Model Preparation
+
+Please download the model parameters before using EIseg. EISeg 0.5.0 provides seven direction models trained on COCO+LVIS, large-scale portrait data, mapping_challenge, MRSpineSeg, Chest Xray, LiTS and Self-built aluminum plate quality inspection data set to meet the labeling needs of generic and portrait scenarios as well as architecture, medical and industrial images. The model architecture corresponds to the network selection module in EISeg interactive tools, and users need to select different network structures and loading parameters in accordance with their own needs.
+
+| Model Type          | Applicable Scenarios                     | Model Architecture | Download Link                                                |
+|---------------------| ---------------------------------------- | ------------------ | ------------------------------------------------------------ |
+| High Performance Model | Image annotation in generic scenarios    | HRNet18_OCR64      | [static_hrnet18_ocr64_cocolvis](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18_ocr64_cocolvis.zip) |
+| Lightweight Model   | Image annotation in generic scenarios    | HRNet18s_OCR48     | [static_hrnet18s_ocr48_cocolvis](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18s_ocr48_cocolvis.zip) |
+| High Performance Model | Annotation in portrait scenarios         | HRNet18_OCR64      | [static_hrnet18_ocr64_human](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18_ocr64_human.zip) |
+| High Performance Model | Image annotation in generic scenarios    | EdgeFlow           | [static_edgeflow_cocolvis](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_edgeflow_cocolvis.zip) |
+| Lightweight Model   | Annotation in portrait scenarios         | HRNet18s_OCR48     | [static_hrnet18s_ocr48_human](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18s_ocr48_human.zip) |
+| Lightweight Model   | Annotation of remote sensing building    | HRNet18s_OCR48     | [static_hrnet18_ocr48_rsbuilding_instance](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18_ocr48_rsbuilding_instance.zip) |
+| High Performance Model | Annotation of chest Xray in medical scenarios | Resnet50_DeeplabV3+   | [static_resnet50_deeplab_chest_xray \*](https://paddleseg.bj.bcebos.com/eiseg/0.5/static_resnet50_deeplab_chest_xray.zip) |
+| Lightweight Model   | Annotation of liver in medical scenarios | HRNet18s_OCR48     | [static_hrnet18s_ocr48_lits](https://paddleseg.bj.bcebos.com/eiseg/0.4/static_hrnet18s_ocr48_lits.zip) |
+| Lightweight Model   | Annotation of Spinal Structures in medical scenarios | HRNet18s_OCR48     | [static_hrnet18s_ocr48_MRSpineSeg](https://paddleseg.bj.bcebos.com/eiseg/0.5/static_hrnet18s_ocr48_MRSpineSeg.zip) |
+| Lightweight Model   | Annotation of Aluminum plate defects in industrial scenarios | HRNet18s_OCR48     | [static_hrnet18s_ocr48_aluminium ](https://paddleseg.bj.bcebos.com/eiseg/0.5/static_hrnet18s_ocr48_aluminium.zip) |
+
+**NOTE**： The downloaded model structure `*.pdmodel` and the corresponding model parameters `*.pdiparams` should be put into the same directory. When loading the model, you only need to decide the location of the model parameter at the end of `*.pdiparams`, and `*.pdmodel` will be loaded automatically. When using `EdgeFlow` model, please turn off `Use Mask`, and check `Use Mask` when adopting other models. For `High Performance Model`, we recommend to utilize the computer with gpu for a smoother annotation experience.
+
+## Using
+
+After opening the software, make the following settings before annotating:
+
+1. **Load Model Parameter**
+
+   Select the appropriate network and load the corresponding model parameters.  After downloading and decompressing the right model and parameters, the model structure `*.pdmodel` and the corresponding model parameters `*.pdiparams` should be put into the same directory, and only the location of the model parameter at the end of `*.pdiparams`need to be selected when loading the model. The initialization of the static model takes some time, please wait patiently until the model is loaded. The correctly loaded model parameters will be recorded in `Recent Model Parameters`, which can be easily switched, and the exiting model parameter will be loaded automatically the next time you open the software.
+
+2. **Load Image**
+
+   Open the image or image folder. Things go well when you see that the main screen image is loaded correctly and the image path is rightly shown in `Data List`.
+
+3. **Add/Load Label**
+
+   Add/load labels. New labels can be created by `Add Label`, which are divided into 4 columns corresponding to pixel value, description, color and deletion. The newly created labels can be saved as txt files by `Save Label List`, and other collaborators can import labels by `Load Label List`. Labels imported by loading will be loaded automatically after restarting the software.
+
+4. **Annotation**
+
+    During interactive annotation, users add positive and negative points with left and right mouse clicks, respectively. After finishing interactive segmentation, you can push Space button and the tool generates a polygon frame around the target border. Users can
+adjust the polygon vertexes to further improve segmentation accuracy.
+
+5. **Autosave**
+
+   You can choose the right folder and have the `autosave` set up, so that the annotated image will be saved automatically when switching images.
+
+Start the annotation when the above are all set up. Here are the commonly used keys/shortcut keys by default, press `E` to modify them as you need.
+
+| Keys/Shortcut Keys                | Function                       |
+| --------------------------------- | ------------------------------ |
+| Left Mouse Button                 | Add Positive Sample Points     |
+| Right Mouse Button                | Add Negative Sample Points     |
+| Middle Mouse Button               | Image Panning                  |
+| Ctrl+Middle Mouse Button（wheel） | Image Zooming                  |
+| S                                 | Previous Image                 |
+| F                                 | Next Image                     |
+| Space                             | Finish Annotation/Switch State |
+| Ctrl+Z                            | Undo                           |
+| Ctrl+Shift+Z                      | Clear                          |
+| Ctrl+Y                            | Redo                           |
+| Ctrl+A                            | Open Image                     |
+| Shift+A                           | Open Folder                    |
+| E                                 | Open Shortcut Key List         |
+| Backspace                         | Delete Polygon                 |
+| Double Click（point）             | Delete Point                   |
+| Double Click（edge）              | Add Point                      |
+
+## Instruction of New Functions
+
+- **Polygon**
+
+  - Click Space key to complete interactive annotation, then appears the polygon boundary.
+  - When you need to continue the interactive process inside the polygon, click Space to switch to interactive mode so the polygon cannot be selected and changed.
+  - The polygon can be deleted. Use the left mouse to drag the anchor point, double-click the anchor point to delete it, and double-click a side to add an anchor point.
+  - With `Keep Maximum Connected Blocks` on, only the largest area will remain in the image, the rest of the small areas will not be displayed and saved.
+
+- **Save Format**
+
+  - Polygons will be recorded and automatically loaded after setting `JSON Save` or `COCO Save`.
+  - With no specified save path, the image is save to the label folder under the current image folder by default.
+  - If there are images with the same name but different suffixes, you can open `labels and images with the same extensions`.
+  - You can also save as grayscale,  pseudo-color or matting image, see tools 7-9 in the toolbar.
+
+- **Generate mask**
+
+  - Labels can be dragged by holding down the second column, and the final generated mask will be overwritten from top to bottom according to the label list.
+
+- **Interface Module**
+
+  - You can select the interface module to be presented in `Display`, and the normal exit status and location of the interface module will be recorded, and loaded automatically when you open it next time.
+
+- **Vertical Segmentation**
+
+  EISeg now supports remote sensing images and medical images segmentation, and additional dependencies need to be installed for their functioning.
+
+  - Install GDAL for remote sensing image segmentation, please refer to [Remote Sensing Segmentation](docs/remote_sensing_en.md)。
+  - Install SimpleITK for medical images segmentation, please refer to [Medical Image Segmentation](docs/medical_en.md)。
+
+- **Scripting Tool**
+
+  EISeg currently provides scripting tools including annotation to PaddleX dataset, delineation of COCO format and semantic labels to instance labels, etc. See [Scripting Tools Usage](https://github.com/PaddlePaddle/PaddleSeg/blob/develop/EISeg/) for more details.