如何在tensorflow数据管道中应用函数将路径转换为使用cv2的数组?

Question

任何帮助都将非常感谢

我正在尝试加载两个包含图像路径及其相应标签的列表。像这样:

p0 = ['a','b',....] #paths to images .tif format
p1 = [1,2,3,......] #paths to images .tif format
labels = [0,1,1,...] #corresponding labels w.r.t both the lists

我用了一个tf。

def TFData(p_0, p_1, batch_size, labels=None, is_train=True):
dset = tf.data.Dataset.from_tensor_slices((p_0,p_1))
if labels is not None:
label = tf.data.Dataset.from_tensor_slices(labels)

AUTO = tf.data.experimental.AUTOTUNE
final_dset = tf.data.Dataset.zip((dset, label))
final_dset = final_dset.batch(batch_size, drop_remainder=is_train).prefetch(AUTO)
return final_dset

这回报:

<PrefetchDataset shapes: (((64,), (64,)), (64,)), types: ((tf.string, tf.string), tf.int32)>

我的问题是如何应用函数将路径转换为数组使用cv2作为图像是。tif文件?这样的结果将是:

<PrefetchDataset shapes: (((64,256,256,3), (64,256,256,3)), (64,)), types: ((tf.float64, tf.float64), tf.int32)>

我使用的是dataset.map。但是它抛出错误:

def to_array(p_0):
im_1 = cv2.imread(p_0,1)
#im = tfio.experimental.image.decode_tiff(paths)
im_1 = cv2.resize(im_1,(img_w,img_h)) #img_w=img_h=256
im_1 = np.asarray(im_1, dtype=np.float64)
im_1 /= 255
return im_1
def parse_fn(p_0):
[p_0,] = tf.py_function(to_array, [p_0], [tf.float64])
return p_0
def TFData(p_0, p_1, batch_size, labels=None, is_train=True):

dset_1 = tf.data.Dataset.from_tensor_slices(p_0)
dset_1 = dset_1.map(parse_fn)
dset_2 = tf.data.Dataset.from_tensor_slices(p_1)
dset_2 = dset_2.map(parse_fn)
if labels is not None:
label = tf.data.Dataset.from_tensor_slices(labels)

AUTO = tf.data.experimental.AUTOTUNE

final_dset = tf.data.Dataset.zip((dset_1, dset_2, label))
final_dset = final_dset.batch(batch_size, drop_remainder=is_train).prefetch(AUTO)
return final_dset
print(train_data) #where train_data is defined as TFData()
<PrefetchDataset shapes: ((<unknown>, <unknown>), (64,)), types: ((tf.float64, tf.float64), tf.int32)>

抛出错误:

for (t,p),l in train_data.as_numpy_iterator():
print(t)
print(p)
print(l)
print(type(t))
break
SystemError: <built-in function imread> returned NULL without setting an error

[[{{node EagerPyFunc}}]] [Op:IteratorGetNext]

任何帮助都将非常感谢

Answer 1

我想你的问题在cv2.imread。您是否检查过函数外部是否正在读取和绘制相应的数据?

请尝试用-1代替

im_1 = cv2.imread(p_0,-1)