def __init__(self, split, config):
# Validate split input
if split != 'train' and split != 'val' and split != 'trainval' and split != 'test':
raise Exception('Please enter valid split variable!')
root = './dataset/VOC2012/'
self.img_path = join(root, 'JPEGImages/')
self.seg_path = join(root, 'SegmentationClass/')
self.split = split
img_set = join(root, 'ImageSets/Segmentation/' + split + '.txt')
with open(img_set) as f:
self.img_list = f.read().rstrip().split('\n')
self.num_images = len(self.img_list)
self.temp_pointer = 0 # First idx of the current batch
self.batch_num = 1
self.max_size = config['max_size']
# Create double side mappings
self.gray_to_rgb, self.rgb_to_gray = colormap()
__author = "buyizhiyou"
__date = "2018-4-26"
#Demo to predict one image,plot results
import numpy as np
import tensorflow as tf
from model import FCN32_test, FCN16_test, FCN8_test
from dataloader import Dataloader, Dataloader_small
from util import seg_gray_to_rgb, colormap
import matplotlib.pyplot as plt
import cv2
import pdb
import os
gray_to_rgb, rgb_to_gray = colormap()
# BGR mean pixel value
MEAN_PIXEL = np.array([103.939, 116.779, 123.68])
CLASSES = ('__background__', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle',
'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train',
'tvmonitor')
config = {
'batch_num': 1,
'iter': 100000,
'num_classes': 21,
'max_size': (640, 640),
'weight_decay': 0.0005,
'base_lr': 0.001,