基于CASME2数据集训练的微表情识别系统-支持摄像头实时检测和图片视频分析-包含面部微表情特征提取与分类算法-采用深度学习框架TensorFlow和Keras实现-集成VGG16.zip

[{"title":"（ 46 个子文件 60.79MB ） 基于CASME2数据集训练的微表情识别系统-支持摄像头实时检测和图片视频分析-包含面部微表情特征提取与分类算法-采用深度学习框架TensorFlow和Keras实现-集成VGG16.zip","children":[{"title":"说明文件.txt <span style='color:#111;'> 856B </span>","children":null,"spread":false},{"title":"附赠资源.docx <span style='color:#111;'> 41.95KB </span>","children":null,"spread":false},{"title":"MicroExpressionRecognition-master","children":[{"title":"recognition_camera.py <span style='color:#111;'> 3.61KB </span>","children":null,"spread":false},{"title":"sdg2y-jxz4o.gif <span style='color:#111;'> 5.11MB </span>","children":null,"spread":false},{"title":"data_split.py <span style='color:#111;'> 2.21KB </span>","children":null,"spread":false},{"title":"eval_top5.py <span style='color:#111;'> 2.08KB </span>","children":null,"spread":false},{"title":"txt_annotation.py <span style='color:#111;'> 2.52KB </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 34.33KB </span>","children":null,"spread":false},{"title":"recognition_img.py <span style='color:#111;'> 3.63KB </span>","children":null,"spread":false},{"title":"predict.py <span style='color:#111;'> 772B </span>","children":null,"spread":false},{"title":"utils","children":[{"title":"utils.py <span style='color:#111;'> 1.45KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 1B </span>","children":null,"spread":false},{"title":"backend","children":[{"title":"__init__.py <span style='color:#111;'> 53B </span>","children":null,"spread":false},{"title":"tensorflow_backend.py <span style='color:#111;'> 2.89KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"tensorflow_backend.cpython-36.pyc <span style='color:#111;'> 3.40KB </span>","children":null,"spread":false},{"title":"__init__.cpython-36.pyc <span style='color:#111;'> 193B </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"dataloader.py <span style='color:#111;'> 4.55KB </span>","children":null,"spread":false},{"title":"callbacks.py <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"dataloader.cpython-36.pyc <span style='color:#111;'> 3.34KB </span>","children":null,"spread":false},{"title":"callbacks.cpython-36.pyc <span style='color:#111;'> 2.88KB </span>","children":null,"spread":false},{"title":"__init__.cpython-36.pyc <span style='color:#111;'> 150B </span>","children":null,"spread":false},{"title":"utils.cpython-36.pyc <span style='color:#111;'> 1.26KB </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"nets","children":[{"title":"__init__.py <span style='color:#111;'> 336B </span>","children":null,"spread":false},{"title":"Loss.py <span style='color:#111;'> 4.99KB </span>","children":null,"spread":false},{"title":"vgg16.py <span style='color:#111;'> 3.40KB </span>","children":null,"spread":false},{"title":"resnet50.py <span style='color:#111;'> 3.98KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"vgg16.cpython-36.pyc <span style='color:#111;'> 1.85KB </span>","children":null,"spread":false},{"title":"mobilenet.cpython-36.pyc <span style='color:#111;'> 2.61KB </span>","children":null,"spread":false},{"title":"resnet50.cpython-36.pyc <span style='color:#111;'> 2.80KB </span>","children":null,"spread":false},{"title":"Loss.cpython-36.pyc <span style='color:#111;'> 4.74KB </span>","children":null,"spread":false},{"title":"__init__.cpython-36.pyc <span style='color:#111;'> 412B </span>","children":null,"spread":false}],"spread":false},{"title":"mobilenet.py <span style='color:#111;'> 3.71KB </span>","children":null,"spread":false}],"spread":true},{"title":"model_data","children":[{"title":"haarcascade_frontalface_alt.xml <span style='color:#111;'> 898.31KB </span>","children":null,"spread":false},{"title":"mobilenet_2_5_224_tf_no_top.h5 <span style='color:#111;'> 2.01MB </span>","children":null,"spread":false},{"title":"cls_classes.txt <span style='color:#111;'> 57B </span>","children":null,"spread":false},{"title":"vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5 <span style='color:#111;'> 56.16MB </span>","children":null,"spread":false}],"spread":true},{"title":"output","children":[{"title":"1.png <span style='color:#111;'> 795.75KB </span>","children":null,"spread":false},{"title":"save.avi <span style='color:#111;'> 411.40KB </span>","children":null,"spread":false}],"spread":false},{"title":"input_test","children":[{"title":"EP02_05.avi <span style='color:#111;'> 499.31KB </span>","children":null,"spread":false}],"spread":false},{"title":"summary.py <span style='color:#111;'> 432B </span>","children":null,"spread":false},{"title":"recognition_video.py <span style='color:#111;'> 4.12KB </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 145B </span>","children":null,"spread":false},{"title":"classification.py <span style='color:#111;'> 5.43KB </span>","children":null,"spread":false},{"title":"eval_top1.py <span style='color:#111;'> 2.03KB </span>","children":null,"spread":false},{"title":"train.py <span style='color:#111;'> 10.59KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.32KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]