这段代码用来对Cambridge Hand Gesture Data set进行整理，将所有的图像重命名并按照类别放置在预定的文件夹中，以便生成TensorFlow需要的TFRecord文件。

cluster.py

import os
import numpy
from random import randint
from PIL import Image

# Get all the image files' path.
homePath = "./images"

# Define locations for different type of data.
for dir_parent in ["train", "test"]:
    os.mkdir(dir_parent)
    for subdir in ["rock", "paper", "scissor", "others"]:
        os.mkdir(dir_parent + "/" + subdir)

# Define code list for classification.
codePaper = ["0000", "0001", "0003", "0004", "0005"]
codeRock = ["0002"]
codeScissor = ["0006", "0007", "0008"]

# Define counter for images
counter = numpy.zeros([2, 4], int)
count = 0

# Step1, rename and split images according to gesture type.
for filePath, _, fileNames in os.walk(homePath):
    for fileName in fileNames:
        # Only process jpeg files
        if ".jpg" in fileName or ".jpeg" in fileName:
            # Use directory names as image ID, so we could tell which gesture it is from the name.

            train_or_test = ""
            if randint(1, 10) <= 8:
                train_or_test = "train"
            else:
                train_or_test = "test"

            typeCode = filePath[-9:-5]
            category = ""
            if typeCode in codePaper:
                category = "paper"
            elif typeCode in codeScissor:
                category = "scissor"
            elif typeCode in codeRock:
                if int(fileName[-8:-4]) >= 30:
                    category = "rock"
                else:
                    category = "others"

            newPath = os.path.join(os.getcwd(), train_or_test, category)

            # Resize and move the file now
            oldFile = os.path.join(filePath, fileName)
            newFileName = filePath[-14:-10] + "-" + filePath[-9:-5] + "-" + filePath[-4:] + "-" + fileName
            newFile = os.path.join(newPath, newFileName)

            im = Image.open(oldFile)
            im = im.resize((32, 32), Image.NEAREST)
            im.save(newFile)

            if train_or_test == "train":
                if category == "rock":
                    counter[0, 0] += 1
                elif category == "paper":
                    counter[0, 1] += 1
                elif category == "scissor":
                    counter[0, 2] += 1
                else:
                    counter[0, 3] += 1
            else:
                if category == "rock":
                    counter[1, 0] += 1
                elif category == "paper":
                    counter[1, 1] += 1
                elif category == "scissor":
                    counter[1, 2] += 1
                else:
                    counter[1, 3] += 1

            count += 1

            if count % 10 == 0:
                print("Images processed: %d" % count)

        else:
            print("Only image files needed, file " + fileName + " ignored.")


# All done, summary up.
print("Total images: %d" % count)
print("Categories: ", counter)