文件结构及意义 VGG16_model:存放训练好的VGG16模型——vgg16_weights_tf_dim_ordering_tf_kernels.h5 main:主文件 - MedicalLargeClassification.py...阅读VGG16的源码可以发现,VGG16是Model结构,而官网文档给的例子是用Sequential结构搭建模型后,将vgg16_weights_tf_dim_ordering_tf_kernels.h5
vgg16') # 加载权重 if weights == 'imagenet': if include_top: weights_path ="vgg16..._weights_tf_dim_ordering_tf_kernels.h5" #weights_path = get_file('vgg16_weights_tf_dim_ordering_tf_kernels.h5...模型下载: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5
首先在顶部定义了两个下载路径: WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16...weights if weights == 'imagenet': if include_top: weights_path = get_file('vgg16
get_source_inputs WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16...load weights if weights == 'imagenet': if include_top: weights_path = get_file('vgg16...WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5...releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5' weights_path = get_file('vgg16
get_source_inputs WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16...weights if weights == 'imagenet': if include_top: weights_path = get_file('vgg16...WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels.h5...releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5' weights_path = get_file('vgg16
weights_th_dim_ordering_th_kernels.h5' TF_WEIGHTS_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16...convert_all_kernels_in_model(model) else: if include_top: weights_path = get_file('vgg16
fine-tuning . 1、导入预训练权重与网络框架 这里keras中文文档是错误的,要看现在的原作者的博客, WEIGHTS_PATH = '/home/ubuntu/keras/animal5/vgg16
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