Add SVCD configs

examples/rs_research/README.md

@@ -110,7 +110,7 @@ class IterativeBIT(nn.Layer):
 2. 包含模型整体逻辑结构的最外层模块须用`@attach`装饰；
 3. 对于变化检测任务，`forward()`方法除`self`参数外还接受两个参数`t1`、`t2`，分别表示第一时相和第二时相影像。
 
-关于模型定义的更多细节请参考[API文档]()。
+关于模型定义的更多细节请参考[文档](https://github.com/PaddlePaddle/PaddleRS/blob/develop/docs/dev/dev_guide.md)。
 
 #### 3.3.2 自定义训练器
 
@@ -145,7 +145,9 @@ class IterativeBIT(BaseChangeDetector):
 2. 与模型一样，训练器也须用`@attach`装饰；
 3. 训练器和模型可以同名。
 
-关于训练器定义的更多细节请参考[API文档]()。
+在本案例中，仅仅重写了训练器的`__init__()`方法。在实际科研过程中，可以通过重写`train()`、`evaluate()`、`default_loss()`等方法定制更加复杂的训练、评估策略或更换默认损失函数。
+
+关于训练器的更多细节请参考[API文档](https://github.com/PaddlePaddle/PaddleRS/blob/develop/docs/apis/train.md)。
 
 ### 3.4 进行参数分析与消融实验
 
@@ -187,7 +189,8 @@ PaddleRS提供了，只需要。`attach_tools.Attach`对象自动。
 
 ### 5.2 展望
 
-耗时，模型大小，FLOPs
+- 本案例对所有参与比较的算法使用了相同的训练超参数，但由于模型之间存在差异，使用统一的超参训练往往难以保证所有模型都能取得较好的效果。在后续工作中，可以对每个对比算法进行调参，使其获得最优精度。
+- 在评估算法效果时，仅仅对比了精度指标，而未对耗时、模型大小、FLOPs等指标进行考量。后续应当从精度和性能两个方面对算法进行综合评估。
 
 ## 参考文献
 

examples/rs_research/configs/levircd/bit.yaml

@@ -1,6 +1,6 @@
 _base_: ./levircd.yaml
 
-save_dir: ./exp/bit/
+save_dir: ./exp/levircd/bit/
 
 model: !Node
     type: BIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter2_gamma01.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter2_gamma01/
+save_dir: ./exp/levircd/custom_model/iter2_gamma01/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter2_gamma02.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter2_gamma02/
+save_dir: ./exp/levircd/custom_model/iter2_gamma02/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter2_gamma05.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter2_gamma05/
+save_dir: ./exp/levircd/custom_model/iter2_gamma05/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter3_gamma01.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter3_gamma01/
+save_dir: ./exp/levircd/custom_model/iter3_gamma01/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter3_gamma02.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter3_gamma02/
+save_dir: ./exp/levircd/custom_model/iter3_gamma02/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter3_gamma05.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter3_gamma05/
+save_dir: ./exp/levircd/custom_model/iter3_gamma05/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/custom_model/iterative_bit_iter3_gamma10.yaml

@@ -1,6 +1,6 @@
 _base_: ../levircd.yaml
 
-save_dir: ./exp/custom_model/iter3_gamma10/
+save_dir: ./exp/levircd/custom_model/iter3_gamma10/
 
 model: !Node
     type: IterativeBIT

examples/rs_research/configs/levircd/fc_ef.yaml

@@ -0,0 +1,6 @@
+_base_: ./levircd.yaml
+
+save_dir: ./exp/levircd/fc_ef/
+
+model: !Node
+    type: FCEarlyFusion

examples/rs_research/configs/levircd/fc_siam_conc.yaml

@@ -0,0 +1,6 @@
+_base_: ./levircd.yaml
+
+save_dir: ./exp/levircd/fc_siam_conc/
+
+model: !Node
+    type: FCSiamConc

examples/rs_research/configs/levircd/fc_siam_diff.yaml

@@ -0,0 +1,6 @@
+_base_: ./levircd.yaml
+
+save_dir: ./exp/levircd/fc_siam_diff/
+
+model: !Node
+    type: FCSiamDiff

examples/rs_research/configs/levircd/levircd.yaml

@@ -52,7 +52,7 @@ transforms:
           args: ['eval']
 download_on: False
 
-num_epochs: 40
+num_epochs: 50
 train_batch_size: 8
 optimizer: !Node
     type: Adam
@@ -62,11 +62,11 @@ optimizer: !Node
             module: paddle.optimizer.lr
             args:
                 learning_rate: 0.002
-                step_size: 30
+                step_size: 35000
                 gamma: 0.2
-save_interval_epochs: 10
-log_interval_steps: 500
-save_dir: ./exp/
+save_interval_epochs: 5
+log_interval_steps: 50
+save_dir: ./exp/levircd/
 learning_rate: 0.002
 early_stop: False
 early_stop_patience: 5

examples/rs_research/configs/levircd/stanet.yaml

@@ -0,0 +1,6 @@
+_base_: ./levircd.yaml
+
+save_dir: ./exp/levircd/stanet/
+
+model: !Node
+    type: STANet

examples/rs_research/configs/svcd/bit.yaml

@@ -0,0 +1,6 @@
+_base_: ./svcd.yaml
+
+save_dir: ./exp/svcd/bit/
+
+model: !Node
+    type: BIT

examples/rs_research/configs/svcd/custom_model.yaml

@@ -0,0 +1,12 @@
+_base_: ./svcd.yaml
+
+save_dir: ./exp/svcd/custom_model/
+
+model: !Node
+    type: IterativeBIT
+    args:
+        num_iters: 3
+        gamma: 0.5
+        num_classes: 2
+        bit_kwargs:
+            in_channels: 4

examples/rs_research/configs/svcd/fc_ef.yaml

@@ -0,0 +1,6 @@
+_base_: ./svcd.yaml
+
+save_dir: ./exp/svcd/fc_ef/
+
+model: !Node
+    type: FCEarlyFusion

examples/rs_research/configs/svcd/fc_siam_conc.yaml

@@ -0,0 +1,6 @@
+_base_: ./svcd.yaml
+
+save_dir: ./exp/svcd/fc_siam_conc/
+
+model: !Node
+    type: FCSiamConc

examples/rs_research/configs/svcd/fc_siam_diff.yaml

@@ -0,0 +1,6 @@
+_base_: ./svcd.yaml
+
+save_dir: ./exp/svcd/fc_siam_diff/
+
+model: !Node
+    type: FCSiamDiff

examples/rs_research/configs/svcd/stanet.yaml

@@ -0,0 +1,6 @@
+_base_: ./svcd.yaml
+
+save_dir: ./exp/svcd/stanet/
+
+model: !Node
+    type: STANet

examples/rs_research/configs/svcd/svcd.yaml

@@ -0,0 +1,74 @@
+# Basic configurations of SVCD dataset
+
+datasets:
+    train: !Node
+        type: CDDataset
+        args: 
+            data_dir: ./data/svcd/
+            file_list: ./data/svcd/train.txt
+            label_list: null
+            num_workers: 2
+            shuffle: True
+            with_seg_labels: False
+            binarize_labels: True
+    eval: !Node
+        type: CDDataset
+        args:
+            data_dir: ./data/svcd/
+            file_list: ./data/svcd/val.txt
+            label_list: null
+            num_workers: 0
+            shuffle: False
+            with_seg_labels: False
+            binarize_labels: True
+transforms:
+    train:
+        - !Node
+          type: DecodeImg
+        - !Node
+          type: RandomFlipOrRotate
+          args:
+            probs: [0.35, 0.35]
+            probsf: [0.5, 0.5, 0, 0, 0]
+            probsr: [0.33, 0.34, 0.33]
+        - !Node
+          type: Normalize
+          args:
+            mean: [0.5, 0.5, 0.5]
+            std: [0.5, 0.5, 0.5]
+        - !Node
+          type: ArrangeChangeDetector
+          args: ['train']
+    eval:
+        - !Node
+          type: DecodeImg
+        - !Node
+          type: Normalize
+          args:
+            mean: [0.5, 0.5, 0.5]
+            std: [0.5, 0.5, 0.5]
+        - !Node
+          type: ArrangeChangeDetector
+          args: ['eval']
+download_on: False
+
+num_epochs: 200
+train_batch_size: 8
+optimizer: !Node
+    type: Adam
+    args:
+        learning_rate: !Node
+            type: StepDecay
+            module: paddle.optimizer.lr
+            args:
+                learning_rate: 0.0004
+                step_size: 87500
+                gamma: 0.1
+save_interval_epochs: 20
+log_interval_steps: 50
+save_dir: ./exp/
+learning_rate: 0.0004
+early_stop: False
+early_stop_patience: 5
+use_vdl: True
+resume_checkpoint: ''

examples/rs_research/custom_model.py

@@ -45,7 +45,7 @@ class IterativeBIT(nn.Layer):
         return logits_list
 
     def _constr_iter_input(self, im, rate_map):
-        return paddle.concat([im.rate_map], axis=1)
+        return paddle.concat([im, rate_map], axis=1)
 
     def _init_rate_map(self, im_shape):
         b, _, h, w = im_shape

examples/rs_research/run_task.py

@@ -2,6 +2,10 @@
 
 import os
 
+# Import cv2 and sklearn before paddlers to solve the
+# "ImportError: dlopen: cannot load any more object with static TLS" issue.
+import cv2
+import sklearn
 import paddle
 import paddlers
 from paddlers import transforms as T

examples/rs_research/scripts/run_benchmark.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+
+set -e 
+
+for dataset in levircd svcd; do
+    config_dir="configs/${dataset}"
+    log_dir="exp/logs/${dataset}"
+
+    mkdir -p "${log_dir}"
+
+    for config_file in $(ls ${config_dir}); do
+        printf '=%.0s' {1..100} && echo
+        echo -e "\033[33m ${config_file} \033[0m"
+        printf '=%.0s' {1..100} && echo
+        python run_task.py train cd --config "${config_dir}/${config_file}" 2>&1 | tee "${log_dir}/${config_file%.*}"
+        echo
+    done
+done

examples/rs_research/scripts/run_parameter_analysis.sh

@@ -0,0 +1,16 @@
+#!/bin/bash
+
+set -e 
+
+CONFIG_DIR='configs/levircd/custom_model'
+LOG_DIR='exp/logs/parameter_analysis'
+
+mkdir -p "${LOG_DIR}"
+
+for config_file in $(ls ${CONFIG_DIR}); do
+    printf '=%.0s' {1..100} && echo
+    echo -e "\033[33m ${config_file} \033[0m"
+    printf '=%.0s' {1..100} && echo
+    python run_task.py train cd --config "${CONFIG_DIR}/${config_file}" 2>&1 | tee "${LOG_DIR}/${config_file%.*}"
+    echo
+done