昇腾杯-变化检测赛道复赛方案分享——PaddleCD

# 清除cell输出结果def clear_output():
    """
    clear output for both jupyter notebook and the console
    """
    import os
    os.system('cls' if os.name == 'nt' else 'clear')    from IPython.display import clear_output as clear
    clear()

# 解压数据!unzip -oq /home/aistudio/data/data107059/train_png.zip -d /home/aistudio/data/src/
!unzip -oq /home/aistudio/data/data107059/test_AB_png.zip -d /home/aistudio/data/src/

# 安装依赖库!pip install -r /home/aistudio/PaddleCD/requirements.txt
clear_output()

# 生成数据集train.txt val.txt# !python /home/aistudio/work/data_generate.py# 直接拷贝已有的数据集划分文件，保证每次训练评价指标相同!cp /home/aistudio/work/train.txt /home/aistudio/data/src/train.txt
!cp /home/aistudio/work/val.txt /home/aistudio/data/src/val.txt

# 模型训练!python /home/aistudio/PaddleCD/train.py \
       --config /home/aistudio/PaddleCD/cd_config/ocrnet.yml \
       --do_eval \
       --use_vdl \
       --iters 8000 \
       --save_interval 200 \
       --save_dir /home/aistudio/data/output \
       --batch_size=8 \
       --log_iters 20 \
       --fp16# 后台训练时，需要清空输出，保证notebook正常导入；notebook训练时，可以不用# clear_output()

# 将最优模型拷贝到/home/aistudio/best_model路径下!mkdir /home/aistudio/best_model/
!cp /home/aistudio/data/output/best_model/model.pdparams /home/aistudio/best_model/model.pdparams
!find /home/aistudio/data/output -name '*.log' -exec cp -t /home/aistudio/best_model/ "{}" +

# 普通测试!python /home/aistudio/PaddleCD/val.py \
       --config /home/aistudio/PaddleCD/cd_config/ocrnet.yml \
       --batch_size 16 \
       --model_path /home/aistudio/best_model/model.pdparams

# 增强测试!python /home/aistudio/PaddleCD/val.py \
       --config /home/aistudio/PaddleCD/cd_config/ocrnet.yml \
       --aug_eval \
       --flip_vertical \
       --batch_size 16 \
       --model_path /home/aistudio/best_model/model.pdparams

!python /home/aistudio/work/data_sta.py

# 增强推理， 推理结果保存在/home/aistudio/data/src/result下!python /home/aistudio/PaddleCD/predict.py \
       --config /home/aistudio/PaddleCD/cd_config/ocrnet.yml \
       --model_path /home/aistudio/best_model2/model.pdparams \
       --image_path /home/aistudio/data/src/test_AB_png/A \
       --image_path2 /home/aistudio/data/src/test_AB_png/B \
       --aug_pred \
       --flip_vertical \
       --batch_size 32 \
       --save_dir /home/aistudio/data/src

from PIL import Imagefrom collections import namedtupleimport matplotlib.pyplot as plt

Cls = namedtuple('cls', ['name', 'id', 'color'])
Clss = [
    Cls('bg', 0, (0, 0, 0)),
    Cls('change', 1, (255, 255, 255)),
]def get_putpalette(Clss, color_other=[0, 0, 0]):
    '''
    灰度图转8bit彩色图
    :param Clss:颜色映射表
    :param color_other:其余颜色设置
    :return:
    '''
    putpalette = []    for cls in Clss:
        putpalette += list(cls.color)
    putpalette += color_other * (255 - len(Clss))    return putpalette

bin_colormap = get_putpalette(Clss)

%matplotlib inline
img1_path = r'/home/aistudio/data/src/test_AB_png/A/1.png'img2_path = r'/home/aistudio/data/src/test_AB_png/B/1.png'pred_path = r'/home/aistudio/data/src/result/1.png'img1 = Image.open(img1_path)
plt.imshow(img1)
plt.show()
img2 = Image.open(img2_path)
plt.imshow(img2)
plt.show()
pred = Image.open(pred_path)
pred.putpalette(bin_colormap)
plt.imshow(pred)
plt.show