list_dirs = os.walk(path)

As an AI language model, I don't have access to the context of your code. However, based on the given line, it seems that the `os.walk()` function is being used to traverse through the directory tree rooted at the specified path (`path`). This function returns a generator that yields a 3-tuple for each directory in the tree. The 3-tuple contains the path to the directory, a list of the directories within that directory, and a list of the files within that directory. The `list_dirs` variable is assigned the generator object returned by the `os.walk()` function.

相关问题

class CardPredictor: def __del__(self): self.save_traindata() def train_svm(self): # 识别英文字母和数字 self.model = SVM(C=1, gamma=0.5) # 识别中文 self.modelchinese = SVM(C=1, gamma=0.5) if os.path.exists("svm.dat"): self.model.load("svm.dat") else: chars_train = [] chars_label = [] for root, dirs, files in os.walk("train\\chars2"): if len(os.path.basename(root)) > 1: continue root_int = ord(os.path.basename(root)) for filename in files: filepath = os.path.join(root, filename) digit_img = cv2.imread(filepath) digit_img = cv2.cvtColor(digit_img, cv2.COLOR_BGR2GRAY) chars_train.append(digit_img) chars_label.append(root_int) chars_train = list(map(deskew, chars_train)) chars_train = preprocess_hog(chars_train) chars_label = np.array(chars_label) self.model.train(chars_train, chars_label) if os.path.exists("svmchinese.dat"): self.modelchinese.load("svmchinese.dat") else: chars_train = [] chars_label = [] for root, dirs, files in os.walk("train\\charsChinese"): if not os.path.basename(root).startswith("zh_"): continue pinyin = os.path.basename(root) index = provinces.index(pinyin) + PROVINCE_START + 1 # 1是拼音对应的汉字 for filename in files: filepath = os.path.join(root, filename) digit_img = cv2.imread(filepath) digit_img = cv2.cvtColor(digit_img, cv2.COLOR_BGR2GRAY) chars_train.append(digit_img) chars_label.append(index) chars_train = list(map(deskew, chars_train)) chars_train = preprocess_hog(chars_train) chars_label = np.array(chars_label) self.modelchinese.train(chars_train, chars_label)

这段代码实现了一个卡牌识别器，使用 SVM 算法来识别卡牌上的数字、英文字母和汉字。它将训练数据从文件中读取，对于数字和英文字母，训练数据位于 "train\\chars2" 文件夹中；对于汉字，训练数据位于 "train\\charsChinese" 文件夹中。训练数据中的每张图片都经过了去倾斜、HOG 特征提取等预处理操作，最后使用 SVM 算法进行训练。训练好的模型可以保存到文件中以便于之后的使用。当程序结束时，会自动保存训练数据。

import os from flask import Flask, render_template, request, redirect, sessions, jsonify from flask_socketio import SocketIO, emit # 导入socketio包 name_space = '/websocket' app = Flask(__name__) app.secret_key = 'secret!' socketio = SocketIO(app, cors_allowed_origins='*') client_query = [] max_restruct_count = 3 current_restruct_count = 0 queue = [] restr_msg = {} is_restructing = False @socketio.on('connect') def on_connect(): client_id = request.sid client_query.append(client_id) socketio.emit('abb', 'hi') print('有新连接id=%s接加入, 当前连接数%d' % (client_id, len(client_query))) global is_restructing, current_restruct_count if current_restruct_count == 0: socketio.emit('status', '0') else: socketio.emit('status', '1') @socketio.on('disconnect') def on_disconnect(): client_query.remove(request.sid) print('有连接id=%s接退出, 当前连接数%d' % (request.sid, len(client_query))) @socketio.on('abc') def on_message(abc): print(abc) def check(): global current_restruct_count if current_restruct_count == 0: socketio.emit('status', '0') else: socketio.emit('status', '1') @socketio.on('output') def start_restruct(dch): return 1 @app.route('/restruct', methods=['POST']) def restruct(): return jsonify({"code": 200, "msg": "processing"}) @app.route('/show_dirs', methods=['POST']) def show_dirs(): des_dir = 'moxingku' dirs_list = [] for root, dirs, files in os.walk(des_dir): for dir_name in dirs: if os.path.join(root, dir_name).count(os.sep) == 1: dirs_list.append(dir_name) return jsonify({"code": 200, "dirs_list": dirs_list}) if __name__ == '__main__': socketio.run(app, host='0.0.0.0', port=5000, debug=False)#allow_unsafe_werkzeug=True) 这段代码如何改可以将开发环境变成生产环境

要将开发环境变为生产环境，你需要进行以下更改：

1. 将 `debug` 参数设置为 `False`，这样可以禁用调试模式。
2. 将 `host` 参数设置为 `0.0.0.0`，以允许外部访问服务器。
3. 将 `port` 参数设置为适当的生产环境端口号，例如 80。

修改后的代码如下所示：

import os
from flask import Flask, render_template, request, redirect, sessions, jsonify
from flask_socketio import SocketIO, emit

name_space = '/websocket'
app = Flask(__name__)
app.secret_key = 'secret!'
socketio = SocketIO(app, cors_allowed_origins='*')
client_query = []

max_restruct_count = 3
current_restruct_count = 0
queue = []
restr_msg = {}

is_restructing = False

@socketio.on('connect')
def on_connect():
    client_id = request.sid
    client_query.append(client_id)
    socketio.emit('abb', 'hi')
    print('有新连接id=%s接加入, 当前连接数%d' % (client_id, len(client_query)))

    global is_restructing, current_restruct_count

    if current_restruct_count == 0:
        socketio.emit('status', '0')
    else:
        socketio.emit('status', '1')

@socketio.on('disconnect')
def on_disconnect():
    client_query.remove(request.sid)
    print('有连接id=%s接退出, 当前连接数%d' % (request.sid, len(client_query)))

@socketio.on('abc')
def on_message(abc):
    print(abc)

def check():
    global current_restruct_count
    if current_restruct_count == 0:
        socketio.emit('status', '0')
    else:
        socketio.emit('status', '1')

@socketio.on('output')
def start_restruct(dch):
    return 1

@app.route('/restruct', methods=['POST'])
def restruct():
    return jsonify({"code": 200, "msg": "processing"})

@app.route('/show_dirs', methods=['POST'])
def show_dirs():
    des_dir = 'moxingku'
    dirs_list = []

    for root, dirs, files in os.walk(des_dir):
        for dir_name in dirs:
            if os.path.join(root, dir_name).count(os.sep) == 1:
                dirs_list.append(dir_name)

    return jsonify({"code": 200, "dirs_list": dirs_list})

if __name__ == '__main__':
    socketio.run(app, host='0.0.0.0', port=80, debug=False)

请确保在生产环境中安装了相应的依赖，并使用适当的方式启动 Flask 应用程序。