- 2021年03月14日

  - 这一版本将数据集和方法的配置方法转换为基于json文件的配置。
  - 一些配套的更改与简化。

Author: lartpang

.gitignore

@@ -273,5 +273,4 @@ gen
 # private files
 /output/
 /untracked/
-/configs/methods/
-/configs/datasets/
+/configs/

configs/__init__.py

@@ -1,8 +1,8 @@
 # -*- coding: utf-8 -*-
 import os
 
-from configs import total_info
 from metrics.sod import cal_cosod_matrics, draw_curves
+from utils.generate_info import get_datasets_info, get_methods_info
 
 """
 Include: Fm Curve/PR Curves/MAE/(max/mean/weighted) Fmeasure/Smeasure/Emeasure
@@ -12,6 +12,13 @@
     But it needs to have uniform naming rules for `pre` and `gt`.
 """
 
+total_info = dict(
+    rgb_cosod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_cosod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_cosod_methods.json",
+    ),
+)
+
 for_pr = True  # 是否绘制pr曲线
 
 # 当前支持rgb_cosod
@@ -21,10 +28,11 @@
 # 存放输出文件的文件夹
 output_path = "./output"
 
-# 针对多个模型评估比较的设置
-dataset_info = data_info["dataset"]
 # 包含所有待比较模型结果的信息和绘图配置的字典
-drawing_info = data_info["method"]["drawing"]
+dataset_info = get_datasets_info(datastes_info_json=data_info["dataset"])
+drawing_info = get_methods_info(
+    methods_info_json=data_info["method"], for_drawing=True, our_name="SINet"
+)
 
 # 用来保存测试结果的文件的路径
 txt_path = os.path.join(output_path, f"{data_type}.txt")
@@ -66,7 +74,7 @@
 # 评估结果保留的小数点后数据的位数
 num_bits = 3
 
-# 是否保留之前的评估记录（针对record_path文件有效）
+# 是否保留之前的评估记录（针对txt_path文件有效）
 resume_record = True
 
 # 在计算指标的时候要跳过的数据集

configs/utils/__init__.py

@@ -1,8 +1,9 @@
 # -*- coding: utf-8 -*-
+
 import os
 
-from configs import total_info
 from metrics.sod import cal_sod_matrics, draw_curves
+from utils.generate_info import get_datasets_info, get_methods_info
 
 """
 Include: Fm Curve/PR Curves/MAE/(max/mean/weighted) Fmeasure/Smeasure/Emeasure
@@ -12,6 +13,21 @@
     But it needs to have uniform naming rules for `pre` and `gt`.
 """
 
+total_info = dict(
+    rgb_sod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_sod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_sod_methods.json",
+    ),
+    rgb_cod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_cod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_cod_methods.json",
+    ),
+    rgbd_sod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgbd_sod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgbd_sod_methods.json",
+    ),
+)
+
 for_pr = True  # 绘制pr曲线还是fm曲线
 
 # 当前支持rgb_cod, rgb_sod, rgbd_sod
@@ -22,8 +38,10 @@
 output_path = "./output"
 
 # 包含所有待比较模型结果的信息和绘图配置的字典
-dataset_info = data_info["dataset"]
-drawing_info = data_info["method"]["drawing"]
+dataset_info = get_datasets_info(datastes_info_json=data_info["dataset"])
+drawing_info = get_methods_info(
+    methods_info_json=data_info["method"], for_drawing=True, our_name="SINet"
+)
 
 # 用来保存测试结果的文件的路径
 txt_path = os.path.join(output_path, f"{data_type}.txt")
@@ -69,7 +87,7 @@
 resume_record = True
 
 # 在计算指标的时候要跳过的数据集
-skipped_datasets = ["COD10K"]
+skipped_datasets = []
 
 cal_sod_matrics(
     data_type=data_type,

configs/utils/config_generator.py

@@ -5,8 +5,8 @@
 import numpy as np
 import scipy.io as scio
 
-from configs import total_info
 from metrics.sod import draw_curves
+from utils.generate_info import get_datasets_info, get_methods_info
 from utils.misc import colored_print, make_dir
 from utils.print_formatter import print_formatter
 from utils.recorders import MetricExcelRecorder, TxtRecorder
@@ -28,6 +28,25 @@
     But it needs to have uniform naming rules for `pre` and `gt`.
 """
 
+total_info = dict(
+    rgb_cosod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_cosod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_cosod_methods.json",
+    ),
+    rgb_sod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_sod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_sod_methods.json",
+    ),
+    rgb_cod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_cod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_cod_methods.json",
+    ),
+    rgbd_sod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgbd_sod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgbd_sod_methods.json",
+    ),
+)
+
 
 def export_valid_npy():
     """
@@ -127,8 +146,11 @@ def export_valid_npy():
     output_path = "./output"
 
     # 包含所有待比较模型结果的信息和绘图配置的字典
-    dataset_info = data_info["dataset"]
-    drawing_info = data_info["method"]["drawing"]
+    # 包含所有待比较模型结果的信息和绘图配置的字典
+    dataset_info = get_datasets_info(datastes_info_json=data_info["dataset"])
+    drawing_info = get_methods_info(
+        methods_info_json=data_info["method"], for_drawing=True, our_name="SINet"
+    )
 
     # 用来保存测试结果的文件的路径
     txt_path = os.path.join(output_path, f"{data_type}.txt")

eval_cosod_all_methods.py

@@ -4,11 +4,26 @@
 
 from tqdm import tqdm
 
-from configs import total_info
+from utils.generate_info import get_datasets_info
 from utils.misc import colored_print, get_gt_pre_with_name, get_name_list, make_dir
 from utils.print_formatter import print_formatter
 from utils.recorders import MetricExcelRecorder, MetricRecorder
 
+total_info = dict(
+    rgb_sod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_sod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_sod_methods.json",
+    ),
+    rgb_cod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgb_cod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgb_cod_methods.json",
+    ),
+    rgbd_sod=dict(
+        dataset="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/json/rgbd_sod.json",
+        method="/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/methods/json/rgbd_sod_methods.json",
+    ),
+)
+
 
 def cal_all_metrics():
     excel_recorder = MetricExcelRecorder(
@@ -98,7 +113,8 @@ def cal_all_metrics():
     make_dir(output_path)
     model_name = "CoNet"  # 待评估的模型名字
     pred_path = data_info["method"]["selecting"][model_name]  # 待评估的预测结果的路径
-    dataset_info = data_info["dataset"]
+    # 包含所有待比较模型结果的信息和绘图配置的字典
+    dataset_info = get_datasets_info(datastes_info_json=data_info["dataset"])
     export_xlsx = False  # 是否导出xlsx文件
     xlsx_path = os.path.join(output_path, "resutls.xlsx")  # xlsx文件的路径
     num_bits = 3  # 评估结果保留的小数点后数据的位数

eval_sod_all_methods.py

@@ -12,6 +12,9 @@ A Python-based salient object detection and video object segmentation evaluation
 
 ## 重要提示
 
+- 2021年03月14日
+  - 这一版本将数据集和方法的配置方法转换为基于json文件的配置。
+  - 一些配套的更改与简化。
 - 2021年03月12日
   - 这一版本正式将sod的评估、绘图代码与配置分离，主要考虑如下
     - 用户的配置是需要调整的，这部分不适宜被git严格的监视，也便于提交后续更新的时候，直接忽略关于配置的更改，即后续更新时，

eval_sod_all_methods_from_mat.py

@@ -0,0 +1,42 @@
+# -*- coding: utf-8 -*-
+# @Time    : 2021/3/14
+# @Author  : Lart Pang
+# @GitHub  : https://github.com/lartpang
+import json
+import os
+import sys
+from importlib import import_module
+
+from mmcv import Config
+
+source_config_root = "/home/lart/Coding/Py-SOD-VOS-EvalToolkit/configs/datasets/py"
+sys.path.insert(0, source_config_root)
+
+source_config_files = os.listdir(source_config_root)
+for source_config_file in source_config_files:
+    source_config_path = os.path.join(source_config_root, source_config_file)
+    if not os.path.isfile(source_config_path):
+        continue
+    print(source_config_path)
+    temp_module_name = os.path.splitext(source_config_file)[0]
+    Config._validate_py_syntax(source_config_path)
+    mod = import_module(temp_module_name)
+
+    total_dict = {}
+    for name, value in mod.__dict__.items():
+        name: str
+        # For Methods
+        # if not name.startswith("_") and isinstance(value, dict):
+        #     total_dict[name] = value
+
+        # For Datasets
+        if not name.startswith("_") and name.endswith("_data") and isinstance(value, dict):
+            total_dict = value
+
+    # delete imported module
+    del sys.modules[temp_module_name]
+
+    with open(
+        f"../datasets/json/{os.path.basename(temp_module_name)}.json", encoding="utf-8", mode="w"
+    ) as f:
+        json.dump(total_dict, f, indent=2)