From 465a83629d2d4880856bdb5e18bf4ef38ac00942 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Wed, 17 Aug 2022 15:18:57 +0800 Subject: [PATCH 01/13] Update set loss docs --- docs/apis/train.md | 6 +++++- docs/dev/dev_guide.md | 4 ++-- 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/docs/apis/train.md b/docs/apis/train.md index 97f55b1..0eac676 100644 --- a/docs/apis/train.md +++ b/docs/apis/train.md @@ -10,23 +10,27 @@ - 一般支持设置`num_classes`、`use_mixed_loss`以及`in_channels`参数,分别表示模型输出类别数、是否使用预置的混合损失以及输入通道数。部分子类如`DSIFN`暂不支持对`in_channels`参数的设置。 - `use_mixed_loss`参将在未来被弃用,因此不建议使用。 +- 可通过`losses`参数指定模型训练时使用的损失函数。`losses`需为一个字典,其中`'types'`键和`'coef'`键对应的值为两个等长的列表,分别表示损失函数对象(一个可调用对象)和损失函数的权重。例如:`losses={'types': [LossType1(), LossType2()], 'coef': [1.0, 0.5]}`在训练过程中将等价于计算如下损失函数:`1.0*LossType1()(logits, labels)+0.5*LossType2()(logits, labels)`,其中`logits`和`labels`分别是模型输出和真值标签。 - 不同的子类支持与模型相关的输入参数,详情请参考[模型定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/rs_models/cd)和[训练器定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/change_detector.py)。 ### 初始化`BaseClassifier`子类对象 - 一般支持设置`num_classes`和`use_mixed_loss`参数,分别表示模型输出类别数以及是否使用预置的混合损失。 - `use_mixed_loss`参将在未来被弃用,因此不建议使用。 +- 可通过`losses`参数指定模型训练时使用的损失函数,传入实参需为`paddlers.models.clas_losses.CombinedLoss`类型对象。 - 不同的子类支持与模型相关的输入参数,详情请参考[模型定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/rs_models/clas)和[训练器定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/classifier.py)。 -### 初始化`Baseetector`子类对象 +### 初始化`BaseDetector`子类对象 - 一般支持设置`num_classes`和`backbone`参数,分别表示模型输出类别数以及所用的骨干网络类型。相比其它任务,目标检测任务的训练器支持设置的初始化参数较多,囊括网络结构、损失函数、后处理策略等方面。 +- 与分割、分类、变化检测等任务不同,检测任务不支持通过`losses`参数指定损失函数。不过对于部分训练器如`PPYOLO`,可通过`use_iou_loss`等参数定制损失函数。 - 不同的子类支持与模型相关的输入参数,详情请参考[模型定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/rs_models/det)和[训练器定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/object_detector.py)。 ### 初始化`BaseSegmenter`子类对象 - 一般支持设置`input_channel`、`num_classes`以及`use_mixed_loss`参数,分别表示输入通道数、输出类别数以及是否使用预置的混合损失。部分模型如`FarSeg`暂不支持对`input_channel`参数的设置。 - `use_mixed_loss`参将在未来被弃用,因此不建议使用。 +- 可通过`losses`参数指定模型训练时使用的损失函数。`losses`需为一个字典,其中`'types'`键和`'coef'`键对应的值为两个等长的列表,分别表示损失函数对象(一个可调用对象)和损失函数的权重。例如:`losses={'types': [LossType1(), LossType2()], 'coef': [1.0, 0.5]}`在训练过程中将等价于计算如下损失函数:`1.0*LossType1()(logits, labels)+0.5*LossType2()(logits, labels)`,其中`logits`和`labels`分别是模型输出和真值标签。 - 不同的子类支持与模型相关的输入参数,详情请参考[模型定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/rs_models/seg)和[训练器定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/segmentor.py)。 ## `train()` diff --git a/docs/dev/dev_guide.md b/docs/dev/dev_guide.md index 55f3980..9076935 100644 --- a/docs/dev/dev_guide.md +++ b/docs/dev/dev_guide.md @@ -64,8 +64,8 @@ Args: 2. 在`paddlers/tasks`目录中找到任务对应的训练器定义文件(例如变化检测任务对应`paddlers/tasks/change_detector.py`)。 3. 在文件尾部追加新的训练器定义。训练器需要继承自相关的基类(例如`BaseChangeDetector`),重写`__init__()`方法,并根据需要重写其他方法。对训练器`__init__()`方法编写的要求如下: - - 对于变化检测、场景分类、目标检测、图像分割任务,`__init__()`方法的第1个输入参数是`num_classes`,表示模型输出类别数;对于变化检测、场景分类、图像分割任务,第2个输入参数是`use_mixed_loss`,表示用户是否使用默认定义的混合损失。 - - `__init__()`的所有输入参数都必须有默认值,且在**取默认值的情况下,模型接收3通道RGB输入**。 + - 对于变化检测、场景分类、目标检测、图像分割任务,`__init__()`方法的第1个输入参数是`num_classes`,表示模型输出类别数;对于变化检测、场景分类、图像分割任务,第2个输入参数是`use_mixed_loss`,表示用户是否使用默认定义的混合损失;对于变化检测、场景分类、图像分割任务,第3个输入参数是`losses`,表示训练过程中使用的损失函数。 + - `__init__()`的所有输入参数都必须有默认值,且在**取默认值的情况下,模型接收3通道RGB输入**、不使用mixed loss、使用`default_loss`定义的损失函数。 - 在`__init__()`中需要更新`params`字典,该字典中的键值对将被用作模型构造时的输入参数。 4. 在全局变量`__all__`中添加新增训练器的类名。 From d990ae60eab6f0d91dd15e7c97c634a14be9cc17 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Wed, 17 Aug 2022 15:19:17 +0800 Subject: [PATCH 02/13] Remove ellipsis --- docs/intro/transforms.md | 45 ++++++++++++++++++++-------------------- 1 file changed, 22 insertions(+), 23 deletions(-) diff --git a/docs/intro/transforms.md b/docs/intro/transforms.md index 6144704..605d238 100644 --- a/docs/intro/transforms.md +++ b/docs/intro/transforms.md @@ -4,29 +4,28 @@ PaddleRS对不同遥感任务需要的数据预处理/数据增强(合称为数据变换)策略进行了有机整合,设计统一的算子。考虑到遥感影像的多波段特性,PaddleRS的大部分数据处理算子均能够处理任意数量波段的输入。PaddleRS目前提供的所有数据变换算子如下表: -| 数据变换算子名 | 用途 | 任务 | ... | -| -------------------- | ------------------------------------------------- | -------- | ---- | -| Resize | 调整输入影像大小。 | 所有任务 | ... | -| RandomResize | 随机调整输入影像大小。 | 所有任务 | ... | -| ResizeByShort | 调整输入影像大小,保持纵横比不变(根据短边计算缩放系数)。 | 所有任务 | ... | -| RandomResizeByShort | 随机调整输入影像大小,保持纵横比不变(根据短边计算缩放系数)。 | 所有任务 | ... | -| ResizeByLong | 调整输入影像大小,保持纵横比不变(根据长边计算缩放系数)。 | 所有任务 | ... | -| RandomHorizontalFlip | 随机水平翻转输入影像。 | 所有任务 | ... | -| RandomVerticalFlip | 随机竖直翻转输入影像。 | 所有任务 | ... | -| Normalize | 对输入影像应用标准化。 | 所有任务 | ... | -| CenterCrop | 对输入影像进行中心裁剪。 | 所有任务 | ... | -| RandomCrop | 对输入影像进行随机中心裁剪。 | 所有任务 | ... | -| RandomScaleAspect | 裁剪输入影像并重新缩放到原始尺寸。 | 所有任务 | ... | -| RandomExpand | 根据随机偏移扩展输入影像。 | 所有任务 | ... | -| Pad | 将输入影像填充到指定的大小。 | 所有任务 | ... | -| MixupImage | 将两幅影像(及对应的目标检测标注)混合在一起作为新的样本。 | 目标检测 | ... | -| RandomDistort | 对输入施加随机色彩变换。 | 所有任务 | ... | -| RandomBlur | 对输入施加随机模糊。 | 所有任务 | ... | -| Dehaze | 对输入图像进行去雾。 | 所有任务 | ... | -| ReduceDim | 对输入图像进行波段降维。 | 所有任务 | ... | -| SelectBand | 对输入影像进行波段选择。 | 所有任务 | ... | -| RandomSwap | 随机交换两个时相的输入影像。 | 变化检测 | ... | -| ... | ... | ... | ... | +| 数据变换算子名 | 用途 | 任务 | +| -------------------- | ------------------------------------------------- | -------- | +| Resize | 调整输入影像大小。 | 所有任务 | +| RandomResize | 随机调整输入影像大小。 | 所有任务 | +| ResizeByShort | 调整输入影像大小,保持纵横比不变(根据短边计算缩放系数)。 | 所有任务 | +| RandomResizeByShort | 随机调整输入影像大小,保持纵横比不变(根据短边计算缩放系数)。 | 所有任务 | +| ResizeByLong | 调整输入影像大小,保持纵横比不变(根据长边计算缩放系数)。 | 所有任务 | +| RandomHorizontalFlip | 随机水平翻转输入影像。 | 所有任务 | +| RandomVerticalFlip | 随机竖直翻转输入影像。 | 所有任务 | +| Normalize | 对输入影像应用标准化。 | 所有任务 | +| CenterCrop | 对输入影像进行中心裁剪。 | 所有任务 | +| RandomCrop | 对输入影像进行随机中心裁剪。 | 所有任务 | +| RandomScaleAspect | 裁剪输入影像并重新缩放到原始尺寸。 | 所有任务 | +| RandomExpand | 根据随机偏移扩展输入影像。 | 所有任务 | +| Pad | 将输入影像填充到指定的大小。 | 所有任务 | +| MixupImage | 将两幅影像(及对应的目标检测标注)混合在一起作为新的样本。 | 目标检测 | +| RandomDistort | 对输入施加随机色彩变换。 | 所有任务 | +| RandomBlur | 对输入施加随机模糊。 | 所有任务 | +| Dehaze | 对输入图像进行去雾。 | 所有任务 | +| ReduceDim | 对输入图像进行波段降维。 | 所有任务 | +| SelectBand | 对输入影像进行波段选择。 | 所有任务 | +| RandomSwap | 随机交换两个时相的输入影像。 | 变化检测 | ## 组合算子 From 9ae4d8ed9096be4f27befd494c57e73cac44c430 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Wed, 17 Aug 2022 15:32:51 +0800 Subject: [PATCH 03/13] Update README.md --- README.md | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 19be9c5..8c97147 100644 --- a/README.md +++ b/README.md @@ -64,30 +64,35 @@ PaddleRS具有以下五大特色:
  • ResNet50-vd
  • MobileNetV3
  • HRNet
  • +
  • ...
  • 语义分割
      -
    • UNet
    • FarSeg
    • +
    • UNet
    • DeepLab V3+
    • +
    • ...
    目标检测
    • PP-YOLO
    • Faster R-CNN
    • YOLOv3
    • +
    • ...
    图像复原
    • DRNet
    • LESRCNN
    • ESRGAN
    • +
    • ...
    变化检测
    • DSIFN
    • STANet
    • ChangeStar
    • +
    • ...
    @@ -114,6 +119,7 @@ PaddleRS具有以下五大特色:
  • ReduceDim
  • SelectBand
  • RandomSwap
  • +
  • ...
  • @@ -122,12 +128,15 @@ PaddleRS具有以下五大特色:
  • coco to mask
  • mask to shpfile
  • mask to geojson
  • +
  • ...
  • 数据预处理
    • 影像切片
    • 影像配准
    • 波段选择
    • +
    • 辐射校正
    • +
    • ...
    @@ -135,7 +144,7 @@ PaddleRS具有以下五大特色:
    • 待更
    - 遥感语义分割
    + 遥感图像分割
    • 待更
    @@ -147,7 +156,7 @@ PaddleRS具有以下五大特色:
    • 待更
    - 遥感影像超分
    + 遥感图像复原
    • 待更
    From 88cf17e028cd790c80215d716592f5e913be14fd Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Sat, 20 Aug 2022 21:25:08 +0800 Subject: [PATCH 04/13] Init res docs --- docs/apis/data.md | 4 ++++ docs/apis/infer.md | 10 ++++++--- docs/apis/train.md | 10 +++++++++ docs/dev/dev_guide.md | 8 +++---- tests/deploy/test_predictor.py | 10 ++++++++- tests/rs_models/test_res_models.py | 36 ++++++++++++++++++++++++++++++ 6 files changed, 70 insertions(+), 8 deletions(-) create mode 100644 tests/rs_models/test_res_models.py diff --git a/docs/apis/data.md b/docs/apis/data.md index 8f8bc4d..ab8a523 100644 --- a/docs/apis/data.md +++ b/docs/apis/data.md @@ -84,6 +84,9 @@ - file list中的每一行应该包含2个以空格分隔的项,依次表示输入影像相对`data_dir`的路径以及[Pascal VOC格式](http://host.robots.ox.ac.uk/pascal/VOC/)标注文件相对`data_dir`的路径。 +### 图像复原数据集`ResDataset` + + ### 图像分割数据集`SegDataset` `SegDataset`定义在:https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/datasets/seg_dataset.py @@ -143,6 +146,7 @@ |`'aux_masks'`|图像分割/变化检测任务中的辅助标签路径或数据。| |`'gt_bbox'`|目标检测任务中的检测框标注数据。| |`'gt_poly'`|目标检测任务中的多边形标注数据。| +|`'target'`|图像复原中的目标影像路径或数据。| ### 组合数据变换算子 diff --git a/docs/apis/infer.md b/docs/apis/infer.md index c7f3d1c..2a5b62d 100644 --- a/docs/apis/infer.md +++ b/docs/apis/infer.md @@ -26,7 +26,7 @@ def predict(self, img_file, transforms=None): 若`img_file`是一个元组,则返回对象为包含下列键值对的字典: ``` -{"label map": 输出类别标签(以[h, w]格式排布),"score_map": 模型输出的各类别概率(以[h, w, c]格式排布)} +{"label_map": 输出类别标签(以[h, w]格式排布),"score_map": 模型输出的各类别概率(以[h, w, c]格式排布)} ``` 若`img_file`是一个列表,则返回对象为与`img_file`等长的列表,其中的每一项为一个字典(键值对如上所示),顺序对应`img_file`中的每个元素。 @@ -51,7 +51,7 @@ def predict(self, img_file, transforms=None): 若`img_file`是一个字符串或NumPy数组,则返回对象为包含下列键值对的字典: ``` -{"label map": 输出类别标签, +{"label_map": 输出类别标签, "scores_map": 输出类别概率, "label_names_map": 输出类别名称} ``` @@ -87,6 +87,10 @@ def predict(self, img_file, transforms=None): 若`img_file`是一个列表,则返回对象为与`img_file`等长的列表,其中的每一项为一个由字典(键值对如上所示)构成的列表,顺序对应`img_file`中的每个元素。 +#### `BaseRestorer.predict()` + + + #### `BaseSegmenter.predict()` 接口形式: @@ -107,7 +111,7 @@ def predict(self, img_file, transforms=None): 若`img_file`是一个字符串或NumPy数组,则返回对象为包含下列键值对的字典: ``` -{"label map": 输出类别标签(以[h, w]格式排布),"score_map": 模型输出的各类别概率(以[h, w, c]格式排布)} +{"label_map": 输出类别标签(以[h, w]格式排布),"score_map": 模型输出的各类别概率(以[h, w, c]格式排布)} ``` 若`img_file`是一个列表,则返回对象为与`img_file`等长的列表,其中的每一项为一个字典(键值对如上所示),顺序对应`img_file`中的每个元素。 diff --git a/docs/apis/train.md b/docs/apis/train.md index 0eac676..4ad1a1e 100644 --- a/docs/apis/train.md +++ b/docs/apis/train.md @@ -26,6 +26,10 @@ - 与分割、分类、变化检测等任务不同,检测任务不支持通过`losses`参数指定损失函数。不过对于部分训练器如`PPYOLO`,可通过`use_iou_loss`等参数定制损失函数。 - 不同的子类支持与模型相关的输入参数,详情请参考[模型定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/rs_models/det)和[训练器定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/object_detector.py)。 +### 初始化`BaseRestorer`子类对象 + + + ### 初始化`BaseSegmenter`子类对象 - 一般支持设置`input_channel`、`num_classes`以及`use_mixed_loss`参数,分别表示输入通道数、输出类别数以及是否使用预置的混合损失。部分模型如`FarSeg`暂不支持对`input_channel`参数的设置。 @@ -174,6 +178,9 @@ def train(self, |`use_vdl`|`bool`|是否启用VisualDL日志。|`True`| |`resume_checkpoint`|`str` \| `None`|检查点路径。PaddleRS支持从检查点(包含先前训练过程中存储的模型权重和优化器权重)继续训练,但需注意`resume_checkpoint`与`pretrain_weights`不得同时设置为`None`以外的值。|`None`| +### `BaseRestorer.train()` + + ### `BaseSegmenter.train()` 接口形式: @@ -315,6 +322,9 @@ def evaluate(self, "mask": 预测得到的掩模图信息} ``` +### `BaseRestorer.evaluate()` + + ### `BaseSegmenter.evaluate()` 接口形式: diff --git a/docs/dev/dev_guide.md b/docs/dev/dev_guide.md index 9076935..9f678af 100644 --- a/docs/dev/dev_guide.md +++ b/docs/dev/dev_guide.md @@ -22,7 +22,7 @@ 在子目录中新建文件,以`{模型名称小写}.py`命名。在文件中编写完整的模型定义。 -新模型必须是`paddle.nn.Layer`的子类。对于图像分割、目标检测和场景分类任务,分别需要遵循[PaddleSeg](https://github.com/PaddlePaddle/PaddleSeg)、[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)和[PaddleClas](https://github.com/PaddlePaddle/PaddleClas)套件中制定的相关规范。**对于变化检测、场景分类和图像分割任务,模型构造时必须传入`num_classes`参数以指定输出的类别数目**。对于变化检测任务,模型定义需遵循的规范与分割模型类似,但有以下几点不同: +新模型必须是`paddle.nn.Layer`的子类。对于图像分割、目标检测、场景分类和图像复原任务,分别需要遵循[PaddleSeg](https://github.com/PaddlePaddle/PaddleSeg)、[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)、[PaddleClas](https://github.com/PaddlePaddle/PaddleClas)和[PaddleGAN](https://github.com/PaddlePaddle/PaddleGAN)套件中制定的相关规范。**对于变化检测、场景分类和图像分割任务,模型构造时必须传入`num_classes`参数以指定输出的类别数目。对于图像复原任务,模型构造时必须传入`rs_factor`参数以指定超分辨率缩放倍数(对于非超分辨率模型,将此参数设置为`None`)。**对于变化检测任务,模型定义需遵循的规范与分割模型类似,但有以下几点不同: - `forward()`方法接受3个输入参数,分别是`self`、`t1`和`t2`,其中`t1`和`t2`分别表示前、后两个时相的输入影像。 - 对于多任务变化检测模型(例如模型同时输出变化检测结果与两个时相的建筑物提取结果),需要指定类的`USE_MULTITASK_DECODER`属性为`True`,同时在`OUT_TYPES`属性中设置模型前向输出的列表中每一个元素对应的标签类型。可参考`ChangeStar`模型的定义。 @@ -64,8 +64,8 @@ Args: 2. 在`paddlers/tasks`目录中找到任务对应的训练器定义文件(例如变化检测任务对应`paddlers/tasks/change_detector.py`)。 3. 在文件尾部追加新的训练器定义。训练器需要继承自相关的基类(例如`BaseChangeDetector`),重写`__init__()`方法,并根据需要重写其他方法。对训练器`__init__()`方法编写的要求如下: - - 对于变化检测、场景分类、目标检测、图像分割任务,`__init__()`方法的第1个输入参数是`num_classes`,表示模型输出类别数;对于变化检测、场景分类、图像分割任务,第2个输入参数是`use_mixed_loss`,表示用户是否使用默认定义的混合损失;对于变化检测、场景分类、图像分割任务,第3个输入参数是`losses`,表示训练过程中使用的损失函数。 - - `__init__()`的所有输入参数都必须有默认值,且在**取默认值的情况下,模型接收3通道RGB输入**、不使用mixed loss、使用`default_loss`定义的损失函数。 + - 对于变化检测、场景分类、目标检测、图像分割任务,`__init__()`方法的第1个输入参数是`num_classes`,表示模型输出类别数。对于变化检测、场景分类、图像分割任务,第2个输入参数是`use_mixed_loss`,表示用户是否使用默认定义的混合损失;第3个输入参数是`losses`,表示训练时使用的损失函数。对于图像复原任务,第1个参数是`losses`,含义同上;第2个参数是`rs_factor`,表示超分辨率缩放倍数。 + - `__init__()`的所有输入参数都必须有默认值,且在**取默认值的情况下,模型接收3通道RGB输入**。 - 在`__init__()`中需要更新`params`字典,该字典中的键值对将被用作模型构造时的输入参数。 4. 在全局变量`__all__`中添加新增训练器的类名。 @@ -78,7 +78,7 @@ Args: ### 2.2 新增数据预处理/数据增强算子 -在`paddlers/transforms/operators.py`中定义新算子,所有算子均继承自`paddlers.transforms.Transform`类。算子的`apply()`方法接收一个字典`sample`作为输入,取出其中存储的相关对象,处理后对字典进行in-place修改,最后返回修改后的字典。在定义算子时,只有极少数的情况需要重写`apply()`方法。大多数情况下,只需要重写`apply_im()`、`apply_mask()`、`apply_bbox()`和`apply_segm()`方法就分别可以实现对输入图像、分割标签、目标框以及目标多边形的处理。 +在`paddlers/transforms/operators.py`中定义新算子,所有算子均继承自`paddlers.transforms.Transform`类。算子的`apply()`方法接收一个字典`sample`作为输入,取出其中存储的相关对象,处理后对字典进行in-place修改,最后返回修改后的字典。在定义算子时,只有极少数的情况需要重写`apply()`方法。大多数情况下,只需要重写`apply_im()`、`apply_mask()`、`apply_bbox()`和`apply_segm()`方法就分别可以实现对图像、分割标签、目标框以及目标多边形的处理。 如果处理逻辑较为复杂,建议先封装为函数,添加到`paddlers/transforms/functions.py`中,然后在算子的`apply*()`方法中调用函数。 diff --git a/tests/deploy/test_predictor.py b/tests/deploy/test_predictor.py index 6283951..c18c51a 100644 --- a/tests/deploy/test_predictor.py +++ b/tests/deploy/test_predictor.py @@ -24,7 +24,7 @@ from testing_utils import CommonTest, run_script __all__ = [ 'TestCDPredictor', 'TestClasPredictor', 'TestDetPredictor', - 'TestSegPredictor' + 'TestResPredictor', 'TestSegPredictor' ] @@ -302,6 +302,14 @@ class TestDetPredictor(TestPredictor): self.assertEqual(len(out_multi_array_t), num_inputs) +@TestPredictor.add_tests +class TestResPredictor(TestPredictor): + MODULE = pdrs.tasks.restorer + + def check_predictor(self, predictor, trainer): + pass + + @TestPredictor.add_tests class TestSegPredictor(TestPredictor): MODULE = pdrs.tasks.segmenter diff --git a/tests/rs_models/test_res_models.py b/tests/rs_models/test_res_models.py new file mode 100644 index 0000000..205696d --- /dev/null +++ b/tests/rs_models/test_res_models.py @@ -0,0 +1,36 @@ +# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import paddlers +from rs_models.test_model import TestModel + +__all__ = ['TestRCANModel'] + + +class TestResModel(TestModel): + def check_output(self, output, target): + pass + + def set_inputs(self): + pass + + def set_targets(self): + pass + + +class TestRCANModel(TestSegModel): + MODEL_CLASS = paddlers.rs_models.res.RCAN + + def set_specs(self): + pass From f80bf7658b40dcbca70b2a5603a6c02d7a9972e5 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Fri, 26 Aug 2022 10:23:16 +0800 Subject: [PATCH 05/13] Update whole picture --- docs/images/whole_picture.png | Bin 234493 -> 230207 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/images/whole_picture.png b/docs/images/whole_picture.png index dcd5945a90e60336ed2181a37329b50a735d719d..0d10a2346d4b33ab14fd49ed46c61f0a4cd562cc 100644 GIT binary patch literal 230207 zcma%jcT^Kw_ckJmfP#X6ihzY8MXFK_O$0-g5<&;1NiU&E301j>fYLiiC-g3%1f)rq zUP1y$4-lk;KtlO~_bq>Y@9(nKtQlBm&Y81kpM9SF>}LpnrJ;O{`VKW28QC@9OGRxm zGD>bTvWp^DE|dP!Z9j04bh-f1R#qS@8@#(t`X$s#A84(vPR2{RzCw2C0zKKECS(^# z?e36WI&V%oR4%am=UV&1qkpv_CnF29C8PLP8$;6h{3n5QoZs{J`C`_E|Mr+g{_ob5 z+*ud@eSJ~n{I-y(F(1;2%H^d2gp7=t{`|OLlQ}|~f*cu8QC`>k!e;s@`8;SVH8Zt1kUQbJiMBFYr&JnG&gDF6<*$>IFv;gpi$EUCGQ95 z*YHPv-}|GQM2YIR-YwxJ!sN-wuLqJ*+#|biMehH5`G`D-o;7FNXRgddd&J4*MpXCx zd#|pOM~dbL2rab7D}A6`+?G%adH1J_M;t+g#K9~a0{QK8w>kgc-3D?C?V_yEyL-@H zVib4V%|C-u1Mgu>loug$JRDYC!G9h?vvtl(r8dhS*r;O+?7>1gb*|KSkh4m=&$JKj z4F7(&>vcE3?b)Bly%{4n=5ON(B<|TXPO~uYN_@KX_Z+TYPz{{scq-RJqzz#CGr6C4 zD6-KW?su`$rShr5_s{1_8fPYm{2$CcP)_*D^)&v=R#6xJmx=ymLy6$n;~W2fL;ly& zFYe2^R6R&^FM zZ9UoMEBF3yHwh$b1D;;~->&qh*P!g{_aqE%_TQ!W2QT2BM9O{YhULdX1`|c;sQ}+PK`nE z`4!~+5^nXtwfHf3ViT;dt^LarRrTG(YcAJ%W7k9|OS1^+QT)-*i*M?nJmA%K%Sln? zw6}e!?#co3t5NlGr{V7{%~4b-oul;lWzPh$5r!GPM=dX_G3mG7m#;q>@2ZB{|Ud8}+8h!z_=Lk7jf z20fL{gv11uH(-69Zjw8G2gT5%Uh9E@4UivX(p{>jD#P}R)#?EX5(`nm{-4) zq8#12>wn+A59V^9BpLHwyc`0(ReGWxPTU&mPev|Jh}o=Z0Z^VS;BN({#SmtcZmg8< zF(h%99zQ>RVxrtwhuZ6~#IHqoyfZsn46#aHN7ttN&cmQ(H8ma0CtA&oJ3&CFrKJ8j zPSj_W{3bLSsp1f_4YhTDUVb~%Nhjg?e;51BAi2~l8rTL$a6KA!1SVIy#098kpxeCh zOrJQ^pjHlt1hWi(r$iZd*|1!ZBRQMC|B=XK?Sq81pTnkpsU;sd!8)9-FIJ~ont3f~ zSB&x3oa?6)SWz(%U1=r$1L2<|*1yrvJsB#P&gC%}Nrl`NdXxH5fD?PX=wo1|UW9Ce zjg%vtvwfG2cy=Dwi&K6ekFC1sgvHB5N^F;<1#7c=wi@Y6n(&*=lR{)9r>iqWfi*GA*nMGVvQ@B4&w697K1Cd$0Dz zCR<$!D#Xees-FpQaT}J;!+sovk#~QS&7Zk%327lZidR7pzxH{NP^IfaC3W}m#3fP7 z6hq^>PvZn0@yW;p&P;c8p0CH7v8`e(o~||qty+u(VwwotAm;U<@xgS9{cJ#0Ea!!& zs?d+_lekz~%mU#csv$;0@>{{i8>+>6S$coESMU81lE@Fy%umgX#QWB{9Vj=)9%p=R z>GUxf$n=q?0##!VGXWZ<(*N1_ojFW1|7T-Fe!2`~oW< zQ`{5Mq`KKY@Ggea=aCT4hNXt96)0>g9E_ROV{xZq^4Ok1Zy_w|nZUxm?_5WZ{L_M) zjF3rv0_frNcjJdlh);Z@1YU?td5c2-jz6)}A9Z8(lk1!f64zZxs zj+A|~e^ng%=7C&-kD7fE7F*j9X}lS+o!<~LbSJeh->IQfy0hMQxw&ZP$k{(8)M+I3fc^KYo zTJRO%@F-f}2DuWcSSmkb)Go7@Y^mY`SYRHFkJX!qaOTaP}4RXGCTquz$3|>9}ot-Am`4bFQ`;r?ttURkO$Fob$O$;U>>hV=X42c z)vkB*>xSY!#=kP4{W9@RuMiyo**W2}y>}s_(%_bZ(d|e{?yV(hG30;Na*)FHAA&yM zza9$Qvv`uJ*z#{=|t4ZzQv1(`&Z9n1k3H{Wgu{vOTn} zdex+7IOGm^bP0W^8Df_H1ho5ujAr+p?+gc7gcU5?0KN29$1&cjZ+6%h3{NfH_T!4J zK6zX`qI)SyZCutXxv7i;j39g!E+@GJe(2OKTh^SutjdqPqmB0XA}Ri6wNiBH3oe9} z;M!yYwwXSaY^!mlNp~e0s_kK11@i?G2@`Zn@KcxAVu|L>d_FLp6uh(P-XEqqHiBZX+V0c9WTd39U}H1aTJZ?eV6}gvVpi$T zuRTs&sXhxk%>zNK(p?TTP*VqyVy%-VCtvTFM#y{p7txmKAJWH=tN}X`iOx;B7VOZ2 zq*m8oqE(<~w?X0N*+eK-)>2M5*AWz1<-5*4Rfj%5hGpp++B^lwK}qEGWtfsB75N@ie8B3NkM z5yzacenjAFECcLy>Bfpb_7FGwDZYldCBrZ$Cf^tL*Y0=La7(MA!u_?3x3XXD3*vy< zjt&EAUcZwqw3#WjD~l$_O_^MbEuwmX-jpUb_!)tQVAlptDajMd>apHV2V{X!KpyAI zmfxOEJ##8+fV~kB@|&_cojbel>9xeAA#2!94gt&6H;?kdKU7zOMh1Dl{Z; z;ph!?TYe%!_{PUitkdARwb-vAYj^#RC0ciPzTCbs6`jR6VeL+d0Ii zP{Niwcfe$@Ez&llw@_SSn$?m(uy&Ma%Z7GC!#X^9>=A<6=>^8fO<)q_-6`4eueg-6NGHX zCbwCZWW`d^L`z4d9)z`Yu0hu7NQA~FW4W%bNB=rluhA~{mH*Pr1^Ml_oMXmrZqD_q zz#QX&+)8$Kd2Y6=s77wBhT-=;h zI1`^ib@n#acZeWE>F|zbF4T?@qye3-?Q5Pdjjrk1-@d&KrPsM%Sb=Vrktp&?FL)3f zi!`i-(P^|0Oq+>T9iQYL9Q;HzcGHz+L8PSLCOVZ>8Sw{}*y&&WPrg}WMZON0-a9N| z$scg5&$ET04GZ#nQ;wz+3`$~0=}4xmVI_CFQJQ@?O$8QUO^nGG4@05>kV<*N$J zv;jn#j#PcU&3ck#{EZ$|OEzijVTK zLFInLQFr`G*la@PpFz$_D^WKf=9KM12v<8kXkH~|K#4D@Au;gVEwJ9p#b(;V+k zobMrT9my#(WM&4Qbi0De4_udNI6W0{uLad_!ftNXv>ds@b)qYES*+Wdbz}D=jUUIt zWk%tqD2BmhQ0b7La&gm6KJ2cu>RD+HXG4b%h5fXCtk#)_W%kU;%VI7naR02+HkFL+ z%J-@F&P*I*R*cS@Q4`WV#p1yK(yoSakjE zi

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docs/apis/data.md | 16 ++++++++ docs/apis/infer.md | 23 ++++++++++- docs/apis/train.md | 68 +++++++++++++++++++++++++++++-- docs/data/tools.md | 24 ++++++++++- docs/dev/dev_guide.md | 9 ++++ docs/intro/data_prep.md | 9 ++++ docs/intro/transforms.md | 2 +- paddlers/tasks/change_detector.py | 20 ++++----- paddlers/tasks/classifier.py | 4 +- paddlers/tasks/object_detector.py | 2 +- paddlers/tasks/restorer.py | 4 +- paddlers/tasks/segmenter.py | 12 +++--- 13 files changed, 168 insertions(+), 28 deletions(-) create mode 100644 docs/intro/data_prep.md diff --git a/README.md b/README.md index be3ebea..4a55317 100644 --- a/README.md +++ b/README.md @@ -200,8 +200,9 @@ PaddleRS目录树中关键部分如下: * [智能标注工具EISeg](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.6/EISeg) * [遥感影像处理工具集](./docs/data/tools.md) * 组件介绍 - * [数据预处理/数据增强](./docs/intro/transforms.md) + * [数据集预处理脚本](./docs/intro/data_prep.md) * [模型库](./docs/intro/model_zoo.md) + * [数据变换算子](./docs/intro/transforms.md) * 模型训练 * [模型训练API说明](./docs/apis/train.md) * 模型部署 diff --git a/docs/apis/data.md b/docs/apis/data.md index ab8a523..6be2e32 100644 --- a/docs/apis/data.md +++ b/docs/apis/data.md @@ -86,6 +86,22 @@ ### 图像复原数据集`ResDataset` +`ResDataset`定义在:https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/datasets/res_dataset.py + +其初始化参数列表如下: + +|参数名称|类型|参数说明|默认值| +|-------|----|--------|-----| +|`data_dir`|`str`|数据集存放目录。|| +|`file_list`|`str`|file list路径。file list是一个文本文件,其中每一行包含一个样本的路径信息。`ResDataset`对file list的具体要求请参见下文。|| +|`transforms`|`paddlers.transforms.Compose`|对输入数据应用的数据变换算子。|| +|`num_workers`|`int` \| `str`|加载数据时使用的辅助进程数。若设置为`'auto'`,则按照如下规则确定使用进程数:当CPU核心数大于16时,使用8个数据读取辅助进程;否则,使用CPU核心数一半数量的辅助进程。|`'auto'`| +|`shuffle`|`bool`|是否随机打乱数据集中的样本。|`False`| +|`sr_factor`|`int` \| `None`|对于超分辨率重建任务,指定为超分辨率倍数;对于其它任务,指定为`None`。|`None`| + +`ResDataset`对file list的要求如下: + +- file list中的每一行应该包含2个以空格分隔的项,依次表示输入影像(例如超分辨率重建任务中的低分辨率影像)相对`data_dir`的路径以及目标影像(例如超分辨率重建任务中的高分辨率影像)相对`data_dir`的路径。 ### 图像分割数据集`SegDataset` diff --git a/docs/apis/infer.md b/docs/apis/infer.md index 2a5b62d..880b5cc 100644 --- a/docs/apis/infer.md +++ b/docs/apis/infer.md @@ -89,7 +89,28 @@ def predict(self, img_file, transforms=None): #### `BaseRestorer.predict()` +接口形式: + +```python +def predict(self, img_file, transforms=None): +``` + +输入参数: + +|参数名称|类型|参数说明|默认值| +|-------|----|--------|-----| +|`img_file`|`list[str\|np.ndarray]` \| `str` \| `np.ndarray`|输入影像数据(NumPy数组形式)或输入影像路径。若需要一次性预测一组影像,以列表包含这些影像的数据或路径(每幅影像对应列表中的一个元素)。|| +|`transforms`|`paddlers.transforms.Compose` \| `None`|对输入数据应用的数据变换算子。若为`None`,则使用训练器在验证阶段使用的数据变换算子。|`None`| + +返回格式: + +若`img_file`是一个字符串或NumPy数组,则返回对象为包含下列键值对的字典: +``` +{"res_map": 模型输出的复原或重建影像(以[h, w, c]格式排布)} +``` + +若`img_file`是一个列表,则返回对象为与`img_file`等长的列表,其中的每一项为一个字典(键值对如上所示),顺序对应`img_file`中的每个元素。 #### `BaseSegmenter.predict()` @@ -190,7 +211,7 @@ def predict(self, |参数名称|类型|参数说明|默认值| |-------|----|--------|-----| -|`img_file`|`list[str\|tuple\|np.ndarray]` \| `str` \| `tuple` \| `np.ndarray`|对于场景分类、目标检测和图像分割任务来说,该参数可为单一图像路径,或是解码后的、排列格式为[h, w, c]且具有float32类型的图像数据(表示为NumPy数组形式),或者是一组图像路径或np.ndarray对象构成的列表;对于变化检测任务来说,该参数可以为图像路径二元组(分别表示前后两个时相影像路径),或是解码后的两幅图像组成的二元组,或者是上述两种二元组之一构成的列表。|| +|`img_file`|`list[str\|tuple\|np.ndarray]` \| `str` \| `tuple` \| `np.ndarray`|对于场景分类、目标检测、图像复原和图像分割任务来说,该参数可为单一图像路径,或是解码后的、排列格式为[h, w, c]且具有float32类型的图像数据(表示为NumPy数组形式),或者是一组图像路径或np.ndarray对象构成的列表;对于变化检测任务来说,该参数可以为图像路径二元组(分别表示前后两个时相影像路径),或是解码后的两幅图像组成的二元组,或者是上述两种二元组之一构成的列表。|| |`topk`|`int`|场景分类模型预测时使用,表示选取模型输出概率大小排名前`topk`的类别作为最终结果。|`1`| |`transforms`|`paddlers.transforms.Compose`\|`None`|对输入数据应用的数据变换算子。若为`None`,则使用从`model.yml`中读取的算子。|`None`| |`warmup_iters`|`int`|预热轮数,用于评估模型推理以及前后处理速度。若大于1,将预先重复执行`warmup_iters`次推理,而后才开始正式的预测及其速度评估。|`0`| diff --git a/docs/apis/train.md b/docs/apis/train.md index 1cfd883..d28aa94 100644 --- a/docs/apis/train.md +++ b/docs/apis/train.md @@ -1,6 +1,6 @@ # PaddleRS训练API说明 -**训练器**封装了模型训练、验证、量化以及动态图推理等逻辑,定义在`paddlers/tasks/`目录下的文件中。为了方便用户使用,PaddleRS为所有支持的模型均提供了继承自父类[`BaseModel`](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/base.py)的训练器,并对外提供数个API。变化检测、场景分类、图像分割以及目标检测任务对应的训练器类型分别为`BaseChangeDetector`、`BaseClassifier`、`BaseDetector`和`BaseSegmenter`。本文档介绍训练器的初始化函数以及`train()`、`evaluate()` API。 +**训练器**封装了模型训练、验证、量化以及动态图推理等逻辑,定义在`paddlers/tasks/`目录下的文件中。为了方便用户使用,PaddleRS为所有支持的模型均提供了继承自父类[`BaseModel`](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/base.py)的训练器,并对外提供数个API。变化检测、场景分类、目标检测、图像复原以及图像分割任务对应的训练器类型分别为`BaseChangeDetector`、`BaseClassifier`、`BaseDetector`、`BaseRestorer`和`BaseSegmenter`。本文档介绍训练器的初始化函数以及`train()`、`evaluate()` API。 ## 初始化训练器 @@ -28,7 +28,9 @@ ### 初始化`BaseRestorer`子类对象 - +- 一般支持设置`sr_factor`参数,表示超分辨率倍数;对于不支持超分辨率重建任务的模型,`sr_factor`设置为`None`。 +- 可通过`losses`参数指定模型训练时使用的损失函数,传入实参需为可调用对象或字典。手动指定的`losses`与子类的`default_loss()`方法返回值必须具有相同的格式。 +- 不同的子类支持与模型相关的输入参数,详情请参考[模型定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/rs_models/res)和[训练器定义](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/tasks/restorer.py)。 ### 初始化`BaseSegmenter`子类对象 @@ -180,6 +182,46 @@ def train(self, ### `BaseRestorer.train()` +接口形式: + +```python +def train(self, + num_epochs, + train_dataset, + train_batch_size=2, + eval_dataset=None, + optimizer=None, + save_interval_epochs=1, + log_interval_steps=2, + save_dir='output', + pretrain_weights='CITYSCAPES', + learning_rate=0.01, + lr_decay_power=0.9, + early_stop=False, + early_stop_patience=5, + use_vdl=True, + resume_checkpoint=None): +``` + +其中各参数的含义如下: + +|参数名称|类型|参数说明|默认值| +|-------|----|--------|-----| +|`num_epochs`|`int`|训练的epoch数目。|| +|`train_dataset`|`paddlers.datasets.ResDataset`|训练数据集。|| +|`train_batch_size`|`int`|训练时使用的batch size。|`2`| +|`eval_dataset`|`paddlers.datasets.ResDataset` \| `None`|验证数据集。|`None`| +|`optimizer`|`paddle.optimizer.Optimizer` \| `None`|训练时使用的优化器。若为`None`,则使用默认定义的优化器。|`None`| +|`save_interval_epochs`|`int`|训练时存储模型的间隔epoch数。|`1`| +|`log_interval_steps`|`int`|训练时打印日志的间隔step数(即迭代数)。|`2`| +|`save_dir`|`str`|存储模型的路径。|`'output'`| +|`pretrain_weights`|`str` \| `None`|预训练权重的名称/路径。若为`None`,则不适用预训练权重。|`'CITYSCAPES'`| +|`learning_rate`|`float`|训练时使用的学习率大小,适用于默认优化器。|`0.01`| +|`lr_decay_power`|`float`|学习率衰减系数,适用于默认优化器。|`0.9`| +|`early_stop`|`bool`|训练过程是否启用早停策略。|`False`| +|`early_stop_patience`|`int`|启用早停策略时的`patience`参数(参见[`EarlyStop`](https://github.com/PaddlePaddle/PaddleRS/blob/develop/paddlers/utils/utils.py))。|`5`| +|`use_vdl`|`bool`|是否启用VisualDL日志。|`True`| +|`resume_checkpoint`|`str` \| `None`|检查点路径。PaddleRS支持从检查点(包含先前训练过程中存储的模型权重和优化器权重)继续训练,但需注意`resume_checkpoint`与`pretrain_weights`不得同时设置为`None`以外的值。|`None`| ### `BaseSegmenter.train()` @@ -284,7 +326,7 @@ def evaluate(self, eval_dataset, batch_size=1, return_details=False): ``` {"top1": top1准确率, - "top5": `top5准确率} + "top5": top5准确率} ``` ### `BaseDetector.evaluate()` @@ -324,6 +366,26 @@ def evaluate(self, ### `BaseRestorer.evaluate()` +接口形式: + +```python +def evaluate(self, eval_dataset, batch_size=1, return_details=False): +``` + +输入参数如下: + +|参数名称|类型|参数说明|默认值| +|-------|----|--------|-----| +|`eval_dataset`|`paddlers.datasets.ResDataset`|评估数据集。|| +|`batch_size`|`int`|评估时使用的batch size(多卡训练时,为所有设备合计batch size)。|`1`| +|`return_details`|`bool`|*当前版本请勿手动设置此参数。*|`False`| + +输出为一个`collections.OrderedDict`对象,包含如下键值对: + +``` +{"psnr": PSNR指标, + "ssim": SSIM指标} +``` ### `BaseSegmenter.evaluate()` diff --git a/docs/data/tools.md b/docs/data/tools.md index f434c49..035832d 100644 --- a/docs/data/tools.md +++ b/docs/data/tools.md @@ -8,8 +8,9 @@ PaddleRS在`tools`目录中提供了丰富的遥感影像处理工具,包括 - `match.py`:用于实现两幅影像的配准。 - `split.py`:用于对大幅面影像数据进行切片。 - `coco_tools/`:COCO工具合集,用于统计处理COCO格式标注文件。 +- `prepare_dataset/`:数据集预处理脚本合集。 -## 使用示例 +## 使用说明 首先请确保您已将PaddleRS下载到本地。进入`tools`目录: @@ -101,3 +102,24 @@ python split.py --image_path {输入影像路径} [--mask_path {真值标签路 - `json_Merge.py`: 将多个json文件合并为一个。 详细使用方法请参见[coco_tools使用说明](coco_tools.md)。 + +### prepare_dataset + +`prepare_dataset`目录中包含一系列数据预处理脚本,主要用于预处理已下载到本地的遥感开源数据集,使其符合PaddleRS训练、验证、测试的标准。 + +在执行脚本前,您可以通过`--help`选项获取帮助信息。例如: + +```shell +python prepare_dataset/prepare_levircd.py --help +``` + +以下列出了脚本中常见的命令行选项: + +- `--in_dataset_dir`:下载到本地的原始数据集所在路径。示例:`--in_dataset_dir downloads/LEVIR-CD`。 +- `--out_dataset_dir`:处理后的数据集存放路径。示例:`--out_dataset_dir data/levircd`。 +- `--crop_size`:对于支持影像裁块的数据集,指定切分的影像块大小。示例:`--crop_size 256`。 +- `--crop_stride`:对于支持影像裁块的数据集,指定切分时滑窗移动的步长。示例:`--crop_stride 256`。 +- `--seed`:随机种子。可用于固定随机数生成器产生的伪随机数序列,从而得到固定的数据集划分结果。示例:`--seed 1919810` +- `--ratios`:对于支持子集随机划分的数据集,指定需要划分的各个子集的样本比例。示例:`--ratios 0.7 0.2 0.1`。 + +您可以在[此文档](https://github.com/PaddlePaddle/PaddleRS/blob/develop/docs/intro/data_prep.md)中查看PaddleRS提供哪些数据集的预处理脚本。 diff --git a/docs/dev/dev_guide.md b/docs/dev/dev_guide.md index 9f678af..e4de181 100644 --- a/docs/dev/dev_guide.md +++ b/docs/dev/dev_guide.md @@ -70,6 +70,15 @@ Args: 4. 在全局变量`__all__`中添加新增训练器的类名。 +需要注意的是,对于图像复原任务,模型的前向、反向逻辑均实现在训练器定义中。对于GAN等需要用到多个网络的模型,训练器的编写请参照如下规范: +- 重写`build_net()`方法,使用`GANAdapter`维护所有网络。`GANAdapter`对象在构造时接受两个列表作为输入:第一个列表中包含所有的生成器,其中第一个元素为主生成器;第二个列表中包含所有的判别器。 +- 重写`default_loss()`方法,构建损失函数。若训练过程中需要用到多个损失函数,推荐以字典的形式组织。 +- 重写`default_optimizer()`方法,构建一个或多个优化器。当`build_net()`返回值的类型为`GANAdapter`时,`parameters`参数为一个字典。其中,`parameters['params_g']`是一个列表,顺序包含各个生成器的state dict;`parameters['params_d']`是一个列表,顺序包含各个判别器的state dict。若构建多个优化器,在返回时应使用`OptimizerAdapter`包装。 +- 重写`run_gan()`方法,该方法接受`net`、`inputs`、`mode`、和`gan_mode`四个参数,用于执行训练过程中的某一个子任务,例如生成器的前向计算、判别器的前向计算等等。 +- 重写`train_step()`方法,在其中编写模型训练过程中一次迭代的具体逻辑。通常的做法是反复调用`run_gan()`,每次调用时都根据需要构造不同的`inputs`、并使其工作在不同的`gan_mode`,并从每次返回的`outputs`字典中抽取有用的字段(如各项损失),汇总至最终结果。 + +GAN训练器的具体例子可以参考`ESRGAN`。 + ## 2 新增数据预处理/数据增强函数或算子 ### 2.1 新增数据预处理/数据增强函数 diff --git a/docs/intro/data_prep.md b/docs/intro/data_prep.md new file mode 100644 index 0000000..6932e6b --- /dev/null +++ b/docs/intro/data_prep.md @@ -0,0 +1,9 @@ +# 数据集预处理脚本 + +## PaddleRS已支持的数据集预处理脚本列表 + +| 任务 | 数据集名称 | 数据集地址 | 预处理脚本 | +|-----|-----------|----------|----------| +| 变化检测 | LEVIR-CD | https://justchenhao.github.io/LEVIR/ | [prepare_levircd.py](https://github.com/PaddlePaddle/PaddleRS/blob/develop/tools/prepare_dataset/prepare_levircd.py) | +| 变化检测 | Season-varying | https://paperswithcode.com/dataset/cdd-dataset-season-varying | [prepare_svcd.py](https://github.com/PaddlePaddle/PaddleRS/blob/develop/tools/prepare_dataset/prepare_svcd.py) | +| 目标检测 | RSOD | https://github.com/RSIA-LIESMARS-WHU/RSOD-Dataset- | [prepare_rsod](https://github.com/PaddlePaddle/PaddleRS/blob/develop/tools/prepare_dataset/prepare_rsod.py) | diff --git a/docs/intro/transforms.md b/docs/intro/transforms.md index c7234de..f568541 100644 --- a/docs/intro/transforms.md +++ b/docs/intro/transforms.md @@ -1,4 +1,4 @@ -# 数据预处理/数据增强 +# 数据变换算子 ## PaddleRS已支持的数据变换算子列表 diff --git a/paddlers/tasks/change_detector.py b/paddlers/tasks/change_detector.py index 7a45172..d79734e 100644 --- a/paddlers/tasks/change_detector.py +++ b/paddlers/tasks/change_detector.py @@ -409,18 +409,18 @@ class BaseChangeDetector(BaseModel): key-value pairs: For binary change detection (number of classes == 2), the key-value pairs are like: - {"iou": `intersection over union for the change class`, - "f1": `F1 score for the change class`, - "oacc": `overall accuracy`, - "kappa": ` kappa coefficient`}. + {"iou": intersection over union for the change class, + "f1": F1 score for the change class, + "oacc": overall accuracy, + "kappa": kappa coefficient}. For multi-class change detection (number of classes > 2), the key-value pairs are like: - {"miou": `mean intersection over union`, - "category_iou": `category-wise mean intersection over union`, - "oacc": `overall accuracy`, - "category_acc": `category-wise accuracy`, - "kappa": ` kappa coefficient`, - "category_F1-score": `F1 score`}. + {"miou": mean intersection over union, + "category_iou": category-wise mean intersection over union, + "oacc": overall accuracy, + "category_acc": category-wise accuracy, + "kappa": kappa coefficient, + "category_F1-score": F1 score}. """ self._check_transforms(eval_dataset.transforms, 'eval') diff --git a/paddlers/tasks/classifier.py b/paddlers/tasks/classifier.py index 23ab154..5756c71 100644 --- a/paddlers/tasks/classifier.py +++ b/paddlers/tasks/classifier.py @@ -380,8 +380,8 @@ class BaseClassifier(BaseModel): Returns: If `return_details` is False, return collections.OrderedDict with key-value pairs: - {"top1": `acc of top1`, - "top5": `acc of top5`}. + {"top1": acc of top1, + "top5": acc of top5}. """ self._check_transforms(eval_dataset.transforms, 'eval') diff --git a/paddlers/tasks/object_detector.py b/paddlers/tasks/object_detector.py index 3086bd5..e954a69 100644 --- a/paddlers/tasks/object_detector.py +++ b/paddlers/tasks/object_detector.py @@ -491,7 +491,7 @@ class BaseDetector(BaseModel): Returns: If `return_details` is False, return collections.OrderedDict with key-value pairs: - {"bbox_mmap":`mean average precision (0.50, 11point)`}. + {"bbox_mmap": mean average precision (0.50, 11point)}. """ if metric is None: diff --git a/paddlers/tasks/restorer.py b/paddlers/tasks/restorer.py index f68264d..5a56c48 100644 --- a/paddlers/tasks/restorer.py +++ b/paddlers/tasks/restorer.py @@ -365,8 +365,8 @@ class BaseRestorer(BaseModel): Returns: If `return_details` is False, return collections.OrderedDict with key-value pairs: - {"psnr": `peak signal-to-noise ratio`, - "ssim": `structural similarity`}. + {"psnr": peak signal-to-noise ratio, + "ssim": structural similarity}. """ diff --git a/paddlers/tasks/segmenter.py b/paddlers/tasks/segmenter.py index b9c586f..8a4c34f 100644 --- a/paddlers/tasks/segmenter.py +++ b/paddlers/tasks/segmenter.py @@ -398,12 +398,12 @@ class BaseSegmenter(BaseModel): Returns: collections.OrderedDict with key-value pairs: - {"miou": `mean intersection over union`, - "category_iou": `category-wise mean intersection over union`, - "oacc": `overall accuracy`, - "category_acc": `category-wise accuracy`, - "kappa": ` kappa coefficient`, - "category_F1-score": `F1 score`}. + {"miou": mean intersection over union, + "category_iou": category-wise mean intersection over union, + "oacc": overall accuracy, + "category_acc": category-wise accuracy, + "kappa": kappa coefficient, + "category_F1-score": F1 score}. """ From 83c51846d955103afd9d3ad15a06c4daa219d07b Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Tue, 30 Aug 2022 20:41:11 +0800 Subject: [PATCH 07/13] Add web demo examples --- examples/README.md | 26 ++++++++++++++++++++++++-- 1 file changed, 24 insertions(+), 2 deletions(-) diff --git a/examples/README.md b/examples/README.md index 14d3864..30ab5d0 100644 --- a/examples/README.md +++ b/examples/README.md @@ -8,9 +8,31 @@ PaddleRS提供从科学研究到产业应用的丰富示例,希望帮助遥感 ## 2 社区贡献案例 -[AI Studio](https://aistudio.baidu.com/aistudio/index)是基于百度深度学习平台飞桨的人工智能学习与实训社区,提供在线编程环境、免费GPU算力、海量开源算法和开放数据,帮助开发者快速创建和部署模型。您可以在AI Studio上探索PaddleRS的更多玩法: +### 2.1 基于PaddleRS的遥感解译平台 -[AI Studio上的PaddleRS相关项目](https://aistudio.baidu.com/aistudio/projectoverview/public?kw=PaddleRS) +#### 小桨神瞳 + + + +- 作者:白菜 +- 代码仓库:https://github.com/CrazyBoyM/webRS + +#### 遥感图像智能解译平台 + +

    + +

    +

    + +

    + +- 作者:HHU-河马海牛队 +- 代码仓库:https://github.com/terayco/Intelligent-RS-System +- 演示视频:https://www.bilibili.com/video/BV1eY4y1u7Eq/?vd_source=75a73fc15a4e8b25195728ee93a5b322 + +### 2.2 AI Studio上的PaddleRS相关项目 + +[AI Studio](https://aistudio.baidu.com/aistudio/index)是基于百度深度学习平台飞桨的人工智能学习与实训社区,提供在线编程环境、免费GPU算力、海量开源算法和开放数据,帮助开发者快速创建和部署模型。您可以[在AI Studio上探索PaddleRS的更多玩法](https://aistudio.baidu.com/aistudio/projectoverview/public?kw=PaddleRS)。 本文档收集了部分由开源爱好者贡献的精品项目: From 76e3fe35a665e69b0707213ff0b4d4184d502f1c Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Tue, 30 Aug 2022 20:48:48 +0800 Subject: [PATCH 08/13] Add unittest of FCCDN --- tests/rs_models/test_cd_models.py | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/tests/rs_models/test_cd_models.py b/tests/rs_models/test_cd_models.py index 3b3e683..e274100 100644 --- a/tests/rs_models/test_cd_models.py +++ b/tests/rs_models/test_cd_models.py @@ -21,7 +21,7 @@ __all__ = [ 'TestBITModel', 'TestCDNetModel', 'TestChangeStarModel', 'TestDSAMNetModel', 'TestDSIFNModel', 'TestFCEarlyFusionModel', 'TestFCSiamConcModel', 'TestFCSiamDiffModel', 'TestSNUNetModel', 'TestSTANetModel', - 'TestChangeFormerModel' + 'TestChangeFormerModel', 'TestFCCDNModel' ] @@ -225,3 +225,14 @@ class TestChangeFormerModel(TestCDModel): dict(**base_spec, decoder_softmax=True), dict(**base_spec, embed_dim=56) ] # yapf: disable + + +class TestFCCDNModel(TestCDModel): + MODEL_CLASS = paddlers.rs_models.cd.FCCDN + + def set_specs(self): + self.specs = [ + dict(in_channels=3, num_classes=2), + dict(in_channels=8, num_classes=2), + dict(in_channels=3, num_classes=8) + ] # yapf: disable \ No newline at end of file From 40088e24e93d7949c3ddfcca6db4b45fda8abe42 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Tue, 30 Aug 2022 20:52:52 +0800 Subject: [PATCH 09/13] Update gifs --- examples/README.md | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/examples/README.md b/examples/README.md index 30ab5d0..68033cd 100644 --- a/examples/README.md +++ b/examples/README.md @@ -20,10 +20,7 @@ PaddleRS提供从科学研究到产业应用的丰富示例,希望帮助遥感 #### 遥感图像智能解译平台

    - -

    -

    - +

    - 作者:HHU-河马海牛队 From 543dbc78783309c785d928ee0dc92f442a20cf05 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Thu, 1 Sep 2022 16:43:40 +0800 Subject: [PATCH 10/13] Update doc --- examples/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/README.md b/examples/README.md index 68033cd..2a0ae03 100644 --- a/examples/README.md +++ b/examples/README.md @@ -20,7 +20,7 @@ PaddleRS提供从科学研究到产业应用的丰富示例,希望帮助遥感 #### 遥感图像智能解译平台

    - +

    - 作者:HHU-河马海牛队 From c4743373e3bc5f0c2b9feb5f149297ebb2bd0524 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Thu, 1 Sep 2022 20:27:08 +0800 Subject: [PATCH 11/13] Fix FCCDN unittest --- tests/rs_models/test_cd_models.py | 19 +++++++++++++++---- tests/rs_models/test_seg_models.py | 7 +++++-- 2 files changed, 20 insertions(+), 6 deletions(-) diff --git a/tests/rs_models/test_cd_models.py b/tests/rs_models/test_cd_models.py index e274100..2f7cc14 100644 --- a/tests/rs_models/test_cd_models.py +++ b/tests/rs_models/test_cd_models.py @@ -32,8 +32,11 @@ class TestCDModel(TestModel): self.assertIsInstance(output, list) self.check_output_equal(len(output), len(target)) for o, t in zip(output, target): - o = o.numpy() - self.check_output_equal(o.shape, t.shape) + if isinstance(o, list): + self.check_output(o, t) + else: + o = o.numpy() + self.check_output_equal(o.shape, t.shape) def set_inputs(self): if self.EF_MODE == 'Concat': @@ -234,5 +237,13 @@ class TestFCCDNModel(TestCDModel): self.specs = [ dict(in_channels=3, num_classes=2), dict(in_channels=8, num_classes=2), - dict(in_channels=3, num_classes=8) - ] # yapf: disable \ No newline at end of file + dict(in_channels=3, num_classes=8), + dict(in_channels=3, num_classes=2, _phase='eval', _stop_grad=True) + ] # yapf: disable + + def set_targets(self): + tar_c2 = [self.get_zeros_array(2), [self.get_zeros_array(1)] * 2] + self.targets = [ + tar_c2, tar_c2, [self.get_zeros_array(8), tar_c2[1]], + [self.get_zeros_array(2)] + ] diff --git a/tests/rs_models/test_seg_models.py b/tests/rs_models/test_seg_models.py index 88fb6e1..a5536a8 100644 --- a/tests/rs_models/test_seg_models.py +++ b/tests/rs_models/test_seg_models.py @@ -25,8 +25,11 @@ class TestSegModel(TestModel): self.assertIsInstance(output, list) self.check_output_equal(len(output), len(target)) for o, t in zip(output, target): - o = o.numpy() - self.check_output_equal(o.shape, t.shape) + if isinstance(o, list): + self.check_output(o, t) + else: + o = o.numpy() + self.check_output_equal(o.shape, t.shape) def set_inputs(self): def _gen_data(specs): From a135b37e99defa19f8474a60cf3158288494d697 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Thu, 1 Sep 2022 20:53:48 +0800 Subject: [PATCH 12/13] Update spatial size in test case --- tests/rs_models/test_cd_models.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/tests/rs_models/test_cd_models.py b/tests/rs_models/test_cd_models.py index 2f7cc14..6deed6b 100644 --- a/tests/rs_models/test_cd_models.py +++ b/tests/rs_models/test_cd_models.py @@ -242,7 +242,12 @@ class TestFCCDNModel(TestCDModel): ] # yapf: disable def set_targets(self): - tar_c2 = [self.get_zeros_array(2), [self.get_zeros_array(1)] * 2] + b = self.DEFAULT_BATCH_SIZE + h = self.DEFAULT_HW[0] // 2 + w = self.DEFAULT_HW[1] // 2 + tar_c2 = [ + self.get_zeros_array(2), [self.get_zeros_array(1, b, h, w)] * 2 + ] self.targets = [ tar_c2, tar_c2, [self.get_zeros_array(8), tar_c2[1]], [self.get_zeros_array(2)] From 8ce8e38dd6574db03e63a96627b16bcc7e7b2751 Mon Sep 17 00:00:00 2001 From: Bobholamovic Date: Sun, 4 Sep 2022 23:25:27 +0800 Subject: [PATCH 13/13] Update gif urls --- examples/README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/examples/README.md b/examples/README.md index 2a0ae03..18f0105 100644 --- a/examples/README.md +++ b/examples/README.md @@ -12,10 +12,13 @@ PaddleRS提供从科学研究到产业应用的丰富示例,希望帮助遥感 #### 小桨神瞳 - +

    + +

    - 作者:白菜 - 代码仓库:https://github.com/CrazyBoyM/webRS +- 演示视频:https://www.bilibili.com/video/BV1W14y1s7fs?vd_source=0de109a09b98176090b8aa3295a45bb6 #### 遥感图像智能解译平台