10 monkey | CNN | Tensorflow | Kaggle

10_monkeys数据集

10_monkeys是kaggle平台上的图片数据集，共有十种猴子的各种照片。根据此数据集应用卷积神经网络完成分类。

在Kaggle平台上的实战

创建储存图片的文件夹路径

# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" 
# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session

导入包

import sklearn
import tensorflow as tf
import matplotlib as mpl
import  matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import pandas as pd
import os 
import sys
import time

from tensorflow import keras

print( tf.__version__)
print(sys.version_info)
for module in mpl, np, pd, sklearn, tf, keras:
    print(module.__name__, module.__version__)

数据集路径

train_dir = "../input/10-monkey-species/training/training"
valid_dir = "../input/10-monkey-species/validation/validation"
label_file = "../input/10-monkey-species/monkey_labels.txt"

print(os.path.exists(train_dir))
print(os.path.</