查看不同网络结构（22）---《深度学习》

查看不同网络的权重名称：

#coding=utf-8from PIL import Imageimport osimport os.pathimport numpy as npimport tensorflow as tfimport tensorflow.contrib.slim as slimimport tensorflow.contrib.slim.nets as netsimport inception_resnet_v2def convert(dir):    filelists=os.listdir(dir)    arr_col=[]    for file in filelists:        file_path=os.path.join(dir,file)        img=Image.open(file_path).resize((299,299)).convert("RGB")        r,g,b=img.split()        r_arr=np.array(r)        g_arr=np.array(g)        b_arr=np.array(b)        img_arr=np.concatenate((r_arr,g_arr,b_arr))        result=img_arr.reshape((299,299,3))        arr_col.append(result)    return arr_coldef convert_3_2_4_dims(arr_):    ret=np.zeros((len(arr_),arr_[0].shape[0],arr_[0].shape[1],arr_[0].shape[2]))    for i in range(len(arr_)):        ret[i,:,:,:]=arr_[i]    return retif __name__=="__main__":    dir="E:/test"    arr_col=convert_3_2_4_dims(convert(dir))    arr_col=arr_col.astype("float32")    #print(arr_col.shape)    with slim.arg_scope(inception_resnet_v2.inception_resnet_v2_arg_scope()):        nets_,end_points_ = inception_resnet_v2.inception_resnet_v2(arr_col,num_classes=1001,is_training=False)    with open("E:/inception_resnet_v2_299_end_points.txt",'w') as f:        for item,term in end_points_.items():            f.write(str(item)+":"+str(term)+'\n')

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