使用tensorflow实现u-net的一个例子

import os

import sys

import numpy as np

import tensorflow as tf

import random

import math

import warnings

import pandas as pd

import cv2

import matplotlib.pyplot as plt



from tqdm import tqdm

from itertools import chain

from skimage.io import imread, imshow, imread_collection, concatenate_images

from skimage.transform import resize

from skimage.morphology import label



warnings.filterwarnings('ignore', category=UserWarning, module='skimage')

seed = 42

random.seed = seed

np.random.seed = seed



# Set some parameters

IMG_WIDTH = 128

IMG_HEIGHT = 128

IMG_CHANNELS = 3

TRAIN_PATH = '../input/stage1_train/'

TEST_PATH = '../input/stage1_test/'



warnings.filterwarnings('ignore', category=UserWarning, module='skimage')

seed = 42

random.seed = seed

np.random.seed = seed



# Get train and test IDs

train_ids = next(os.walk(TRAIN_PATH))[1]

test_ids = next(os.walk(TEST_PATH))[1]





# Get and resize train images and masks

images = np.zeros((len(train_ids), IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS), dtype=np.uint8)

labels = np.zeros((len(train_ids), IMG_HEIGHT, IMG_WIDTH, 1), dtype=np.bool)

print('Getting and resizing train images and masks ... ')

sys.stdout.flush()

for n, id_ in tqdm(enumerate(train_ids), total=len(train_ids)):

    path = TRAIN_PATH + id_

    img = imread(path + '/images/' + id_ + '.png')[:,:,:IMG_CHANNELS]

    img = resize(img, (IMG_HEIGHT, IMG_WIDTH), mode='constant', preserve_range=True)

    images[n] = img

    mask = np.zeros((IMG_HEIGHT, IMG_WIDTH, 1), dtype=np.bool)

    for mask_file in next(os.walk(path + '/masks/'))[2]:

        mask_ = imread(path + '/masks/' + mask_file)

        mask_ = np.expand_dims(resize(mask_, (IMG_HEIGHT, IMG_WIDTH), mode='constant', 

                                      preserve_range=True), axis=-1)

        mask = np.maximum(mask, mask_)

    labels[n] = mask



X_train = images

Y_train = labels



# Get and resize test images

X_test = np.zeros((len(test_ids), IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS), dtype=np.uint8)

sizes_test = []

print('Getting and resizing test images ... ')

sys.stdout.flush()

for n, id_ in tqdm(enumerate(test_ids), total=len(test_ids)):

    path = TEST_PATH + id_

    img = imread(path + '/images/' + id_ + '.png')[:,:,:IMG_CHANNELS]

    sizes_test.append([img.shape[0], img.shape[1]])

    img = resize(img, (IMG_HEIGHT, IMG_WIDTH), mode='constant', preserve_range=True)

    X_test[n] = img



print('Done!')