unet_d8g_222f.py 文件源码

def get_masks(scans,masks_list):
    #%matplotlib inline
    scans1=scans.copy()
    maxv=255
    masks=np.zeros(shape=(scans.shape[0],1,img_rows,img_cols))
    for i_m in range(len(masks_list)):
        for i in range(-masks_list[i_m][3],masks_list[i_m][3]+1):
            for j in range(-masks_list[i_m][3],masks_list[i_m][3]+1):
                masks[masks_list[i_m][0],0,masks_list[i_m][2]+i,masks_list[i_m][1]+j]=1
        for i1 in range(-masks_list[i_m][3],masks_list[i_m][3]+1):
            scans1[masks_list[i_m][0],0,masks_list[i_m][2]+i1,masks_list[i_m][1]+masks_list[i_m][3]]=maxv=255
            scans1[masks_list[i_m][0],0,masks_list[i_m][2]+i1,masks_list[i_m][1]-masks_list[i_m][3]]=maxv=255
            scans1[masks_list[i_m][0],0,masks_list[i_m][2]+masks_list[i_m][3],masks_list[i_m][1]+i1]=maxv=255
            scans1[masks_list[i_m][0],0,masks_list[i_m][2]-masks_list[i_m][3],masks_list[i_m][1]+i1]=maxv=255
    for i in range(scans.shape[0]):
        print ('scan '+str(i))
        f, ax = plt.subplots(1, 2,figsize=(10,5))
        ax[0].imshow(scans1[i,0,:,:],cmap=plt.cm.gray)
        ax[1].imshow(masks[i,0,:,:],cmap=plt.cm.gray)
        plt.show()
    return(masks)