加入星計(jì)劃,您可以享受以下權(quán)益:

  • 創(chuàng)作內(nèi)容快速變現(xiàn)
  • 行業(yè)影響力擴(kuò)散
  • 作品版權(quán)保護(hù)
  • 300W+ 專業(yè)用戶
  • 1.5W+ 優(yōu)質(zhì)創(chuàng)作者
  • 5000+ 長(zhǎng)期合作伙伴
立即加入

智慧教室—基于人臉表情識(shí)別的考試防作弊系統(tǒng)

08/23 09:14
2796
服務(wù)支持:
技術(shù)交流群

完成交易后在“購(gòu)買成功”頁(yè)面掃碼入群,即可與技術(shù)大咖們分享疑惑和經(jīng)驗(yàn)、收獲成長(zhǎng)和認(rèn)同、領(lǐng)取優(yōu)惠和紅包等。

虛擬商品不可退

當(dāng)前內(nèi)容為數(shù)字版權(quán)作品,購(gòu)買后不支持退換且無(wú)法轉(zhuǎn)移使用。

加入交流群
掃碼加入
獲取工程師必備禮包
參與熱點(diǎn)資訊討論
放大
實(shí)物圖
相關(guān)方案
  • 方案介紹
    • 課堂專注度分析
    • 作弊檢測(cè)
    • 下載權(quán)重
    • 使用
    • 部分源碼
  • 相關(guān)文件
  • 推薦器件
  • 相關(guān)推薦
  • 電子產(chǎn)業(yè)圖譜
申請(qǐng)入駐 產(chǎn)業(yè)圖譜

需要源碼的朋友請(qǐng)私信我!!?。?/p>

智慧教室—基于人臉表情識(shí)別的考試防作弊系統(tǒng)

課堂專注度及考試作弊系統(tǒng)、課堂動(dòng)態(tài)點(diǎn)名,情緒識(shí)別、表情識(shí)別和人臉識(shí)別結(jié)合

課堂專注度分析

課堂專注度+表情識(shí)別
在這里插入圖片描述

作弊檢測(cè)

關(guān)鍵點(diǎn)計(jì)算方法

轉(zhuǎn)頭(probe)+低頭(peep)+傳遞物品(passing)
在這里插入圖片描述
側(cè)面的傳遞物品識(shí)別
在這里插入圖片描述

邏輯回歸關(guān)鍵點(diǎn)

在這里插入圖片描述

下載權(quán)重

1、Halpe dataset (136 keypoints)

  • 放到detection_system/checkpoints

2、Human-ReID based tracking (Recommended)
Currently the best performance tracking model. Paper coming soon.

Getting started
Download human reid model and place it into AlphaPose/trackers/weights/.

Then simply run alphapose with additional flag --pose_track

You can try different person reid model by modifing cfg.arch and cfg.loadmodel in ./trackers/tracker_cfg.py.

If you want to train your own reid model, please refer to this project
3. Yolo Detector
Download the object detection model manually: yolov3-spp.weights(Google Drive | Baidu pan). Place it into detector/yolo/data.

4. face boxes 預(yù)訓(xùn)練權(quán)重
google drive

放到face_recog/weights文件夾下
5. 其他
人臉識(shí)別:dlib_face_recognition_resnet_model_v1.dat

  • detection_system/face_recog/weights
    人臉對(duì)齊:shape_predictor_68_face_landmarks.dat
  • detection_system/face_recog/weights
    作弊動(dòng)作分類器:cheating_detector_rfc_kp.pkl
  • detection_system/weights

使用

運(yùn)行setup.py安裝必要內(nèi)容

python setup.py build develop

運(yùn)行demo_inference.py
將detection_system設(shè)置為source root
在這里插入圖片描述
使用攝像頭運(yùn)行程序

python demo_inference.py --vis --webcam 0

部分源碼

import os
import platform
import subprocess
import time

import numpy as np
from Cython.Build import cythonize
from setuptools import Extension, find_packages, setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension

MAJOR = 0
MINOR = 3
PATCH = 0
SUFFIX = ''
SHORT_VERSION = '{}.{}.{}{}'.format(MAJOR, MINOR, PATCH, SUFFIX)

version_file = 'alphapose/version.py'


def readme():
    with open('README.md') as f:
        content = f.read()
    return content


def get_git_hash():
    def _minimal_ext_cmd(cmd):
        # construct minimal environment
        env = {}
        for k in ['SYSTEMROOT', 'PATH', 'HOME']:
            v = os.environ.get(k)
            if v is not None:
                env[k] = v
        # LANGUAGE is used on win32
        env['LANGUAGE'] = 'C'
        env['LANG'] = 'C'
        env['LC_ALL'] = 'C'
        out = subprocess.Popen(
            cmd, stdout=subprocess.PIPE, env=env).communicate()[0]
        return out

    try:
        out = _minimal_ext_cmd(['git', 'rev-parse', 'HEAD'])
        sha = out.strip().decode('ascii')
    except OSError:
        sha = 'unknown'

    return sha


def get_hash():
    if os.path.exists('.git'):
        sha = get_git_hash()[:7]
    elif os.path.exists(version_file):
        try:
            from alphapose.version import __version__
            sha = __version__.split('+')[-1]
        except ImportError:
            raise ImportError('Unable to get git version')
    else:
        sha = 'unknown'

    return sha


def write_version_py():
    content = """# GENERATED VERSION FILE
# TIME: {}

__version__ = '{}'
short_version = '{}'
"""
    sha = get_hash()
    VERSION = SHORT_VERSION + '+' + sha

    with open(version_file, 'w') as f:
        f.write(content.format(time.asctime(), VERSION, SHORT_VERSION))


def get_version():
    with open(version_file, 'r') as f:
        exec(compile(f.read(), version_file, 'exec'))
    return locals()['__version__']


def make_cython_ext(name, module, sources):
    extra_compile_args = None
    if platform.system() != 'Windows':
        extra_compile_args = {
            'cxx': ['-Wno-unused-function', '-Wno-write-strings']
        }

    extension = Extension(
        '{}.{}'.format(module, name),
        [os.path.join(*module.split('.'), p) for p in sources],
        include_dirs=[np.get_include()],
        language='c++',
        extra_compile_args=extra_compile_args)
    extension, = cythonize(extension)
    return extension


def make_cuda_ext(name, module, sources):
    return CUDAExtension(
        name='{}.{}'.format(module, name),
        sources=[os.path.join(*module.split('.'), p) for p in sources],
        extra_compile_args={
            'cxx': [],
            'nvcc': [
                '-D__CUDA_NO_HALF_OPERATORS__',
                '-D__CUDA_NO_HALF_CONVERSIONS__',
                '-D__CUDA_NO_HALF2_OPERATORS__',
            ]
        })


def get_ext_modules():
    ext_modules = []
    # only windows visual studio 2013+ support compile c/cuda extensions
    # If you force to compile extension on Windows and ensure appropriate visual studio
    # is intalled, you can try to use these ext_modules.
    force_compile = False
    if platform.system() != 'Windows' or force_compile:
        ext_modules = [
            make_cython_ext(
                name='soft_nms_cpu',
                module='detector.nms',
                sources=['src/soft_nms_cpu.pyx']),
            make_cuda_ext(
                name='nms_cpu',
                module='detector.nms',
                sources=['src/nms_cpu.cpp']),
            make_cuda_ext(
                name='nms_cuda',
                module='detector.nms',
                sources=['src/nms_cuda.cpp', 'src/nms_kernel.cu']),
            make_cuda_ext(
                name='roi_align_cuda',
                module='alphapose.utils.roi_align',
                sources=['src/roi_align_cuda.cpp', 'src/roi_align_kernel.cu']),
            make_cuda_ext(
                name='deform_conv_cuda',
                module='alphapose.models.layers.dcn',
                sources=[
                    'src/deform_conv_cuda.cpp',
                    'src/deform_conv_cuda_kernel.cu'
                ]),
            make_cuda_ext(
                name='deform_pool_cuda',
                module='alphapose.models.layers.dcn',
                sources=[
                    'src/deform_pool_cuda.cpp',
                    'src/deform_pool_cuda_kernel.cu'
                ]),
        ]
    return ext_modules


def get_install_requires():
    install_requires = [
        'six', 'terminaltables', 'scipy==1.1.0',
        'opencv-python', 'matplotlib', 'visdom',
        'tqdm', 'tensorboardx', 'easydict',
        'pyyaml',
        'torch>=1.1.0', 'torchvision>=0.3.0',
        'munkres', 'timm==0.1.20', 'natsort'
    ]
    # official pycocotools doesn't support Windows, we will install it by third-party git repository later
    if platform.system() != 'Windows':
        install_requires.append('pycocotools==2.0.0')
    return install_requires


def is_installed(package_name):
    from pip._internal.utils.misc import get_installed_distributions
    for p in get_installed_distributions():
        if package_name in p.egg_name():
            return True
    return False


if __name__ == '__main__':
    write_version_py()
    setup(
        name='alphapose',
        version=get_version(),
        description='Code for AlphaPose',
        long_description=readme(),
        keywords='computer vision, human pose estimation',
        url='https://github.com/MVIG-SJTU/AlphaPose',
        packages=find_packages(exclude=('data', 'exp',)),
        package_data={'': ['*.json', '*.txt']},
        classifiers=[
            'Development Status :: 4 - Beta',
            'License :: OSI Approved :: Apache Software License',
            'Operating System :: OS Independent',
            'Programming Language :: Python :: 2',
            'Programming Language :: Python :: 2.7',
            'Programming Language :: Python :: 3',
            'Programming Language :: Python :: 3.4',
            'Programming Language :: Python :: 3.5',
            'Programming Language :: Python :: 3.6',
        ],
        license='GPLv3',
        python_requires=">=3",
        setup_requires=['pytest-runner', 'numpy', 'cython'],
        tests_require=['pytest'],
        install_requires=get_install_requires(),
        ext_modules=get_ext_modules(),
        cmdclass={'build_ext': BuildExtension},
        zip_safe=False)
    # Windows need pycocotools here: https://github.com/philferriere/cocoapi#subdirectory=PythonAPI
    if platform.system() == 'Windows' and not is_installed('pycocotools'):
        print("nInstall third-party pycocotools for Windows...")
        cmd = 'python -m pip install git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI'
        os.system(cmd)
    if not is_installed('cython_bbox'):
        print("nInstall `cython_bbox`...")
        cmd = 'python -m pip install git+https://github.com/yanfengliu/cython_bbox.git'
        os.system(cmd)

博客主頁(yè):https://blog.csdn.net/weixin_51141489,需要源碼或相關(guān)資料實(shí)物的友友請(qǐng)關(guān)注、點(diǎn)贊,私信吧!

  • 聯(lián)系方式.txt

推薦器件

更多器件
器件型號(hào) 數(shù)量 器件廠商 器件描述 數(shù)據(jù)手冊(cè) ECAD模型 風(fēng)險(xiǎn)等級(jí) 參考價(jià)格 更多信息
CC430F5137IRGZ 1 Texas Instruments 16-Bit ultra-low-power CC430 Sub 1 GHz wireless MCU with 12-Bit ADC, 32kB Flash and 4kB RAM 48-VQFN -40 to 85

ECAD模型

下載ECAD模型
$7.53 查看
S29AL016J70TFI020 1 Cypress Semiconductor Flash, 1MX16, 70ns, PDSO48, TSOP-48
$10.3 查看
LAN8720AI-CP-ABC 1 Microchip Technology Inc Ethernet Transceiver

ECAD模型

下載ECAD模型
$1.26 查看

相關(guān)推薦

電子產(chǎn)業(yè)圖譜