我正在尝试计算二元类彩色图像分类问题中的正，真负，假正，假负比率。
我有二进制类，面部和背景彩色图像，并且必须使用MLP对其进行分类。
ValueError：要求检索元素0，但序列的长度为0
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in _method_wrapper(self, *args, **kwargs)
128 raise ValueError('{} is not supported in multi-worker mode.'.format(
129 method.__name__))
--> 130 return method(self, *args, **kwargs)
131
132 return tf_decorator.make_decorator(
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in predict(self, x, batch_size, verbose, steps, callbacks, max_queue_size, workers, use_multiprocessing)
1577 use_multiprocessing=use_multiprocessing,
1578 model=self,
-> 1579 steps_per_execution=self._steps_per_execution)
1580
1581 # Container that configures and calls `tf.keras.Callback`s.
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py in __init__(self, x, y, sample_weight, batch_size, steps_per_epoch, initial_epoch, epochs, shuffle, class_weight, max_queue_size, workers, use_multiprocessing, model, steps_per_execution)
1115 use_multiprocessing=use_multiprocessing,
1116 distribution_strategy=ds_context.get_strategy(),
-> 1117 model=model)
1118
1119 strategy = ds_context.get_strategy()
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py in __init__(self, x, y, sample_weights, shuffle, workers, use_multiprocessing, max_queue_size, model, **kwargs)
914 max_queue_size=max_queue_size,
915 model=model,
--> 916 **kwargs)
917
918 @staticmethod
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py in __init__(self, x, y, sample_weights, workers, use_multiprocessing, max_queue_size, model, **kwargs)
784 # Since we have to know the dtype of the python generator when we build the
785 # dataset, we have to look at a batch to infer the structure.
--> 786 peek, x = self._peek_and_restore(x)
787 peek = self._standardize_batch(peek)
788 peek = _process_tensorlike(peek)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py in _peek_and_restore(x)
918 @staticmethod
919 def _peek_and_restore(x):
--> 920 return x[0], x
921
922 def _handle_multiprocessing(self, x, workers, use_multiprocessing,
/usr/local/lib/python3.6/dist-packages/keras_preprocessing/image/iterator.py in __getitem__(self, idx)
55 'but the Sequence '
56 'has length {length}'.format(idx=idx,
---> 57 length=len(self)))
58 if self.seed is not None:
59 np.random.seed(self.seed + self.total_batches_seen)
ValueError: Asked to retrieve element 0, but the Sequence has length 0
test_face_dir = "/content/test/TESTSET/face"
test_background_dir = "/content/test/TESTSET/background"
# Face DG
test_datagen_face = ImageDataGenerator(rescale=1./255)
test_generator_face = test_datagen_face.flow_from_directory(
test_face_dir,
target_size=img_window[:2],
batch_size=batch_size,
class_mode='binary',
color_mode='rgb'
)
# Background DG
test_datagen_background = ImageDataGenerator(rescale=1./255)
test_generator_background = test_datagen_background.flow_from_directory(
test_background_dir,
target_size=img_window[:2],
batch_size=batch_size,
class_mode='binary',
color_mode='rgb'
)
#-----------------------------------------
prediction_face = simpleMLP.predict(test_generator_face)
prediction_background = simpleMLP.predict(test_generator_background)
#-----------------------------------------
# th = 0.5 #threshold
# Face
prediction_face[prediction_face>=th]=1
prediction_face[prediction_face<th]=0
pred_face = np.squeeze(prediction_face)
print('pred shape: ', pred_face.shape,int(np.sum(pred_face)))
# Background
prediction_background[prediction_background>=th]=1
prediction_background[prediction_background<th]=0
pred_background = np.squeeze(prediction_background)
print('pred shape: ', pred_background.shape,int(np.sum(pred_background)))
答案 0 :(得分：0)
生成错误是因为我正在使用html {
font-size: 62.5%;
background-color: var(--color-tertiary);
overflow-x: hidden; // My svg is really big and it overflows page, so I need to use this
}
/***************** HEADER **********************/
.header{
width: 100vw;
height: 100vh;
background-position: center;
background-size: cover;
position: relative;
&__logo{ // this is the svg
position: absolute;
top: 0;
left: 30rem;
width: 180rem;
z-index: -1; // I use z-index to make sure that moving svg is in the background of the page
-webkit-animation:spin 4s linear infinite;
-moz-animation:spin 4s linear infinite;
animation:spin 500s linear infinite;
@-moz-keyframes spin { 100% { -moz-transform: rotate(360deg); } }
@-webkit-keyframes spin { 100% { -webkit-transform: rotate(360deg); } }
@keyframes spin { 100% { -webkit-transform: rotate(360deg);} }
}
&__wrapper{
z-index: 10;
}
}
，而我在其中指定的是一个图像文件夹而不是两个文件夹人脸和背景就我而言，当我选择包含两个文件夹的父文件夹时，这个问题就消失了。
任何一种计算真阳性，真阴性，假阳性，假阴性的方法地面真相如下：
class_mode='binary'