在多标签 U-net 中,python,image-processing,keras,image-segmentation,scikit-image"/>
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python - 键错误：在多标签 U-net 中

问题描述

我有一个图像作为输入和两个掩码，我使用了多标签 Unet，训练过程没有任何问题，但是当我尝试获取预测 Id 时遇到了测试生成器的错误 (KeyError: ) 我使用了 cod

def testGenerator(test_path= "data/membrane/test/image",num_image = 1584,target_size = (224,224),flag_multi_class = False,as_gray = False):
for i in range(num_image):
    img = io.imread(os.path.join(test_path,"%d.jpg"%i),as_gray = as_gray)
    img = img / 255.
    img = trans.resize(img,target_size)
    img = np.reshape(img,img.shape) if (not flag_multi_class) else img
    img = np.reshape(img,(1,)+img.shape)
    yield img

对于我使用的可视化

def labelVisualize(num_class,color_dict,img):
     img = img[:,:,0] if len(img.shape) == 3 else img
     img_out = np.zeros(img.shape + (3,))
     for i in range(num_class):
     img_out[img == i,:] = color_dict[i]
     return img_out / 255


def saveResult(save_path,npyfile,flag_multi_class = False,num_class = 2):
    for i,item in enumerate(npyfile):
         img = labelVisualize(num_class,COLOR_DICT,item) if flag_multi_class else item[:,:,0]
         io.imsave(os.path.join(save_path,"%d_predict.tif"%(i)), os.path.join(save_path,"%d_predict.tif"%(i)),skimage.img_as_ubyte(img))

回溯如图：

KeyError                       Traceback (most recent call last)
<ipython-input-29-60fe459f67b9> in <module>
      4 results = model.predict_generator(testGene,10,verbose=1)
      5 #saveResult("data/membrane/test/results",results)
----> 6 saveResult("data/membrane/test/results/road",results)
      7 saveResult("data/membrane/test/results/cl",results)

<ipython-input-26-6c6016bc75cc> in saveResult(save_path, npyfile, flag_multi_class, num_class)
      26     for i,item in enumerate(npyfile):
      27         img = labelVisualize(num_class,COLOR_DICT,item) if  flag_multi_class else item[:,:,0]
 ---> 28         io.imsave(os.path.join(save_path,"%d_predict.tif"%    (i)), os.path.join(save_path,"%d_predict.tif"%  (i)),skimage.img_as_ubyte(img))

/anaconda3/lib/python3.6/site-packages/skimage/io/_io.py in imsave(fname, arr, plugin, **plugin_args)
     137         if fname.lower().endswith(('.tiff', '.tif')):
     138             plugin = 'tifffile'
 --> 139     if is_low_contrast(arr):
     140         warn('%s is a low contrast image' % fname)
     141     if arr.dtype == bool:

  /anaconda3/lib/python3.6/site-packages/skimage/exposure/exposure.py in is_low_contrast(image, fraction_threshold, lower_percentile, upper_percentile, method)
     501         image = rgb2gray(image)
     502 
 --> 503     dlimits = dtype_limits(image, clip_negative=False)
     504     limits = np.percentile(image, [lower_percentile, upper_percentile])
     505     ratio = (limits[1] - limits[0]) / (dlimits[1] - dlimits[0])

 /anaconda3/lib/python3.6/site-packages/skimage/util/dtype.py in dtype_limits(image, clip_negative)
      55         warn('The default of `clip_negative` in `skimage.util.dtype_limits` '
      56              'will change to `False` in version 0.15.')
 ---> 57     imin, imax = dtype_range[image.dtype.type]
      58     if clip_negative:
      59         imin = 0

KeyError: <class 'numpy.str_'>

我需要为测试数据集中的每个图像获取两个预测掩码并将其保存到单独的文件夹中，解决此问题的任何想法将不胜感激，提前谢谢

标签： pythonimage-processingkerasimage-segmentationscikit-image

解决方案

您将相同的参数os.path.join(save_path,"%d_predict.tif"%(i))两次传递给imsave()，但它应该只传递一次。这就是为什么没有任何作用的原因，因为当imsave()检查数组包含什么类型的数据时，数组参数实际上是第二次的文件名，这没有意义。

只将文件路径传递给imsave().

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