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期末作业mmsegmentation
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期末作业mmsegmentation
期末作业mmsegmentation
用户4968用户49682025年10月29日修改
数据集
1.
数据集分析
1.
分析图像均值、标准差、不同类别像素数量。
数据分析导包 && 基本绘图的设置
import os
import json
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
from tqdm import tqdm
from torch.utils.data import Dataset, DataLoader
import torchvision.transforms as transforms
from collections import defaultdict, Counter
import pandas as pd
plt.style.use('default')
sns.set_palette("husl")
plt.rcParams['figure.dpi'] = 200
plt.rcParams['savefig.dpi'] = 200
class CityscapesConfig:
"""Cityscapes dataset configuration class"""
def __init__(self):
# Cityscapes 19 main classes
self.classes = [
'road', 'sidewalk', 'building', 'wall', 'fence',
'pole', 'traffic light', 'traffic sign', 'vegetation', 'terrain',
'sky', 'person', 'rider', 'car', 'truck',
'bus', 'train', 'motorcycle', 'bicycle'
]
# Class ID mapping (19 main classes)
self.class_ids = {
7: 0, 8: 1, 11: 2, 12: 3, 13: 4,
17: 5, 19: 6, 20: 7, 21: 8, 22: 9,
23: 10, 24: 11, 25: 12, 26: 13, 27: 14,
28: 15, 31: 16, 32: 17, 33: 18
}
# Color mapping (for visualization)
self.colors = [
(128/255, 64/255, 128/255), # road
(244/255, 35/255, 232/255), # sidewalk
(70/255, 70/255, 70/255), # building
(102/255, 102/255, 156/255), # wall
(190/255, 153/255, 153/255), # fence
(153/255, 153/255, 153/255), # pole
(250/255, 170/255, 30/255), # traffic light
(220/255, 220/255, 0/255), # traffic sign
(107/255, 142/255, 35/255), # vegetation
(152/255, 251/255, 152/255), # terrain
(70/255, 130/255, 180/255), # sky
(220/255, 20/255, 60/255), # person
(255/255, 0/255, 0/255), # rider
(0/255, 0/255, 142/255), # car
(0/255, 0/255, 70/255), # truck
(0/255, 60/255, 100/255), # bus
(0/255, 80/255, 100/255), # train
(0/255, 0/255, 230/255), # motorcycle
(119/255, 11/255, 32/255) # bicycle
]