Python：使用opennsfw2对图片/视频进行鉴黄识别

pip install opennsfw2

import opennsfw2 as n2

# 将自动下载预训练模型 open_nsfw_weights.h5 到 C:\Users\Administrator\.opennsfw2\weights
# pip install opennsfw2

# 单张预测
image_path = '1.jpg'
nsfw_probability = n2.predict_image(image_path)
print(nsfw_probability)
# 0.16282974183559418

# 批量预测
image_paths = ['1.jpg', '2.jpg']
nsfw_probabilities = n2.predict_images(image_paths)
print(nsfw_probabilities)
# [0.16282965242862701, 0.8638442158699036]

import opennsfw2 as n2

video_path = '1.mp4'
elapsed_seconds, nsfw_probabilities = n2.predict_video_frames(video_path)
for second, probability in zip(elapsed_seconds, nsfw_probabilities):
    print(f'{second:.2f}s: {probability * 100:.0f} %')
# 0.03s: 1%
# ...
# 10.01s: 87.00%
# ...
# 10.64s: 69.00%

import numpy as np
from PIL import Image
from opennsfw2._model import make_open_nsfw_model
from opennsfw2._image import preprocess_image, Preprocessing

image_path = '1.jpg'
image = preprocess_image(Image.open(image_path), Preprocessing.YAHOO)
model = make_open_nsfw_model()
nsfw_probability = float(model.predict(np.expand_dims(image, 0), batch_size=1)[0][1])
print(nsfw_probability)
# 0.16282974183559418

import time
import numpy as np
import tkinter as tk
from pathlib import Path
from tkinter import filedialog
from tkinter import messagebox
from PIL import ImageTk, Image

from opennsfw2._model import make_open_nsfw_model
from opennsfw2._image import preprocess_image, Preprocessing

begin = time.time()
model = make_open_nsfw_model()  # 加载模型
elapsed = time.time() - begin  # 加载模型耗时
initialdir = Path.cwd()  # 初始化目录，可切换为图片Path.home() / 'Pictures'
img = None  # 当前打开的图片


def scale(size, width=None, height=None):
    """获取按比例缩放后的宽高"""
    if not width and not height:
        width, height = size
    if not width or not height:
        _width, _height = size
        height = width * _height / _width if width else height
        width = height * _width / _height if height else width
    return int(width), int(height)


def img_resize(event=None):
    """显示图片"""
    global img
    if img:
        _img = img.resize(scale(img.size, height=win.winfo_height()))
        _img = ImageTk.PhotoImage(_img)
        label.config(image=_img)
        label.image = _img


def on_closing():
    """关闭事件"""
    if messagebox.askokcancel('关闭', '是否退出程序？'):
        win.destroy()


def open_file(event=None):
    """打开图片"""
    global initialdir
    global img
    file_path = filedialog.askopenfilename(title='选择图片', initialdir=initialdir,
                                           filetypes=[('image files', ('.png', '.jpg', '.jpeg', '.gif'))])
    if file_path:
        statusbar.config(text='正在加载...')
        statusbar.update_idletasks()
        begin = time.time()
        path = Path(file_path)
        initialdir = path.parent
        img = Image.open(file_path)
        img_resize()
        _img = preprocess_image(Image.open(file_path), Preprocessing.YAHOO)
        probability = float(model.predict(np.expand_dims(_img, 0), batch_size=1)[0][1])
        print(probability)
        end = time.time()
        statusbar.config(text=f'{path.name} 耗时: {end - begin:.2f}s 概率: {probability * 100:.2f} %')


win = tk.Tk()
win.title('黄图检测')  # 标题
menu = tk.Menu(win)
menu.add_command(label='打开', command=open_file)
win.config(menu=menu)
win.bind('<Configure>', img_resize)
win.geometry('600x300+300+300')
win.minsize(200, 200)
win.protocol('WM_DELETE_WINDOW', on_closing)
statusbar = tk.Label(win, text=f'加载模型耗时: {elapsed:.2f}s', bd=1, relief=tk.SUNKEN, anchor=tk.W, name='statusbar')
statusbar.pack(side=tk.BOTTOM, fill=tk.X)
label = tk.Label(win, text='双击打开图片')
label.bind('<Double-Button-1>', open_file)
label.pack(fill=tk.BOTH, expand=True)
win.mainloop()

import time
import threading
import tkinter as tk
from pathlib import Path
from tkinter import filedialog
from tkinter import messagebox
from timeit import default_timer as timer

import imageio
import numpy as np
from PIL import ImageTk, Image

from opennsfw2._model import make_open_nsfw_model
from opennsfw2._image import preprocess_image, Preprocessing

# pip install imageio-ffmpeg

begin = time.time()
model = make_open_nsfw_model()  # 加载模型
elapsed = time.time() - begin  # 加载模型耗时
initialdir = Path.cwd()  # 初始化目录，可切换为图片Path.home() / 'Pictures'
reader = None  # 视频读取器

accum_time = 0
curr_fps = 0
last_fps = 0
prev_time = timer()


def on_closing():
    """关闭事件"""
    if messagebox.askokcancel('关闭', '是否退出程序？'):
        win.destroy()


def play():
    global reader
    global prev_time, accum_time, curr_fps
    for image in reader:
        image = Image.fromarray(image)
        frame_image = ImageTk.PhotoImage(image)
        label.config(image=frame_image)
        label.image = frame_image
        _img = preprocess_image(image, Preprocessing.YAHOO)
        probability = float(model.predict(np.expand_dims(_img, 0), batch_size=1)[0][1])

        # FPS
        curr_time = timer()
        exec_time = curr_time - prev_time
        prev_time = curr_time
        accum_time = accum_time + exec_time
        curr_fps = curr_fps + 1
        if accum_time > 1:
            accum_time = accum_time - 1
            last_fps = curr_fps
            curr_fps = 0
            statusbar.config(text=f'概率: {probability * 100:.2f} % FPS: {last_fps}')


def open_file(event=None):
    """打开视频"""
    global initialdir
    global reader
    file_path = filedialog.askopenfilename(title='选择视频', initialdir=initialdir,
                                           filetypes=[('Select files', ('.mp4', '.mkv', '.avi', '.wmv'))])
    if file_path:
        statusbar.config(text='正在加载...')
        statusbar.update_idletasks()
        path = Path(file_path)
        initialdir = path.parent
        reader = imageio.get_reader(path)
        thread = threading.Thread(target=play, daemon=True)
        thread.start()


win = tk.Tk()
win.title('黄图检测')  # 标题
menu = tk.Menu(win)
menu.add_command(label='打开', command=open_file)
win.config(menu=menu)
win.geometry('1280x720+300+300')
win.minsize(200, 200)
win.protocol('WM_DELETE_WINDOW', on_closing)
statusbar = tk.Label(win, text=f'加载模型耗时: {elapsed:.2f}s', bd=1, relief=tk.SUNKEN, anchor=tk.W, name='statusbar')
statusbar.pack(side=tk.BOTTOM, fill=tk.X)
label = tk.Label(win, text='双击打开视频')
label.bind('<Double-Button-1>', open_file)
label.pack(fill=tk.BOTH, expand=True)
win.mainloop()

import io

import pyglet
import numpy as np
from PIL import Image
from opennsfw2._model import make_open_nsfw_model
from opennsfw2._image import preprocess_image, Preprocessing

# pip install pyglet

model = make_open_nsfw_model()
filename = '1.mp4'
source = pyglet.media.load(filename)
video_format = source.video_format
width, height = video_format.width, video_format.height
title = 'Video Player'
window = pyglet.window.Window(width, height, title)
player = pyglet.media.Player()
player.queue(source)
player.play()


@window.event
def on_draw():
    window.clear()
    if player.source and player.source.video_format:
        player.get_texture().blit(0, 0, width=width, height=height)
        image_data = player.get_texture().get_image_data()
        pitch = -(image_data.width * len('RGB'))
        data = image_data.get_data('RGB', pitch)
        _img = preprocess_image(Image.frombytes('RGB', (width, height), data, 'raw'), Preprocessing.YAHOO)
        probability = float(model.predict(np.expand_dims(_img, 0), batch_size=1)[0][1])
        print(probability)


pyglet.app.run()

效率分析：
get_data() 0.941 s
frombytes() 0.001 s
preprocess_image() 0.006 s
predict() 0.052 s