eval_all_sod_methods.py

# -*- coding: utf-8 -*-

import os

from metrics 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

NOTE:
* Our method automatically calculates the intersection of `pre` and `gt`.
    But it needs to have uniform naming rules for `pre` and `gt`.
"""

total_info = dict(
    rgb_sod=dict(
        dataset="/home/lart/Coding/GIT/PySODEvalToolkit/configs/datasets/json/rgb_sod.json",
        method="/home/lart/Coding/GIT/PySODEvalToolkit/configs/methods/json/rgb_sod_methods.json",
    ),
    rgb_cod=dict(
        dataset="/home/lart/Coding/GIT/PySODEvalToolkit/configs/datasets/json/rgb_cod.json",
        method="/home/lart/Coding/GIT/PySODEvalToolkit/configs/methods/json/rgb_cod_methods.json",
    ),
    rgbd_sod=dict(
        dataset="/home/lart/Coding/GIT/PySODEvalToolkit/configs/datasets/json/rgbd_sod.json",
        method="/home/lart/Coding/GIT/PySODEvalToolkit/configs/methods/json/rgbd_sod_methods.json",
    ),
)

for_drawing = False
for_pr = True  # 绘制pr曲线还是fm曲线

# 当前支持rgb_cod, rgb_sod, rgbd_sod
data_type = "rgbd_sod"
data_info = total_info[data_type]

# 存放输出文件的文件夹
output_path = "./output"
if not os.path.exists(output_path):
    os.mkdir(output_path)

# 包含所有数据集信息的字典
dataset_info = get_datasets_info(
    datastes_info_json=data_info["dataset"],
    # exclude_datasets=["STEREO797"],
)
# 包含所有待比较模型结果的信息和绘图配置的字典
drawing_info = get_methods_info(
    methods_info_json=data_info["method"],
    for_drawing=for_drawing,
    our_name="",
    # exclude_methods=["UCNet_ABP", "UCNet_CVAE"],
)

# 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")
xlsx_path = os.path.join(output_path, f"{data_type}.xlsx")

# 是否将评估结果到npy文件中，该文件可用来绘制pr和fm曲线
save_npy = True
# 保存曲线指标数据的文件路径
curves_npy_path = os.path.join(output_path, data_type + "_" + "curves.npy")
metrics_npy_path = os.path.join(output_path, data_type + "_" + "metrics.npy")

row_num = 1

# 不同曲线的绘图配置
axes_setting = {
    # pr曲线的配置
    "pr": {
        # 横坐标标签
        "x_label": "Recall",
        # 纵坐标标签
        "y_label": "Precision",
        # 横坐标显示范围
        "x_lim": (0.1, 1),
        # 纵坐标显示范围
        "y_lim": (0.1, 1),
    },
    # fm曲线的配置
    "fm": {
        # 横坐标标签
        "x_label": "Threshold",
        # 纵坐标标签
        "y_label": r"F$_{\beta}$",
        # 横坐标显示范围
        "x_lim": (0, 1),
        # 纵坐标显示范围
        "y_lim": (0, 0.9),
    },
}
# 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txt_path文件有效）
resume_record = True

cal_sod_matrics.cal_sod_matrics(
    data_type=data_type,
    txt_path=txt_path,
    resume_record=resume_record,
    xlsx_path=xlsx_path,
    drawing_info=drawing_info,
    dataset_info=dataset_info,
    save_npy=save_npy,
    curves_npy_path=curves_npy_path,
    metrics_npy_path=metrics_npy_path,
    num_bits=num_bits,
)

if for_drawing:
    draw_curves.draw_curves(
        for_pr=for_pr,
        axes_setting=axes_setting,
        curves_npy_path=curves_npy_path,
        row_num=row_num,
        drawing_info=drawing_info,
        dataset_info=dataset_info,
    )