我正在尝试使用便携式计算机作为我的树莓派项目faceRecognition和speechSynthesis的服务器。因此，我创建了一个程序，该程序首先加载两个模型，然后等待请求到来。但是，当我启动程序时，最初FaceRecognition模型成功加载，但是随后在加载speechSynthesis模型时，它对tf.saver给出了error。代码：
服务器-
def findFaceMatch():
image_file = request.files.get("imagefile")
image_file.save("image.jpg")
print("sent for check")
response = face_match_demo.recognizeFace(os.path.join(os.getcwd(),"image.jpg"))
return response, 200
@api.route("/synthesize/<string:text>")
def synthesizeVoice(text):
print(text)
with open("F:/file.wav", 'wb') as f:
f.write(synthesizer.synthesize(text))
return send_from_directory("F:/","file.wav", as_attachment=True), 200
面部识别-
import tensorflow as tf
import numpy as np
from . import facenet
from .align import detect_face
import cv2
import imutils
import os
import pickle
import time
minsize = 20
threshold = [0.6, 0.7, 0.7]
factor = 0.709
margin = 44
input_image_size = 160
def load_models(session):
global sess
sess = session
global pnet, rnet, onet
pnet, rnet, onet = detect_face.create_mtcnn(sess, os.path.join(os.getcwd(),"Face_recognition","align"))
facenet.load_model(os.path.join(os.getcwd(),"Face_recognition","20170512-110547\\20170512-110547.pb"))
global images_placeholder
images_placeholder = tf.get_default_graph().get_tensor_by_name("input:0")
global embeddings
embeddings = tf.get_default_graph().get_tensor_by_name("embeddings:0")
global phase_train_placeholder
phase_train_placeholder = tf.get_default_graph().get_tensor_by_name("phase_train:0")
global embedding_size
embedding_size = embeddings.get_shape()[1]
def getFace(img):
faces = []
img_size = np.asarray(img.shape)[0:2]
bounding_boxes, _ = detect_face.detect_face(img, minsize, pnet, rnet, onet, threshold, factor)
if not len(bounding_boxes) == 0:
for face in bounding_boxes:
if face[4] > 0.50:
det = np.squeeze(face[0:4])
bb = np.zeros(4, dtype=np.int32)
bb[0] = np.maximum(det[0] - margin / 2, 0)
bb[1] = np.maximum(det[1] - margin / 2, 0)
bb[2] = np.minimum(det[2] + margin / 2, img_size[1])
bb[3] = np.minimum(det[3] + margin / 2, img_size[0])
cropped = img[bb[1]:bb[3], bb[0]:bb[2], :]
resized = cv2.resize(cropped, (input_image_size,input_image_size),interpolation=cv2.INTER_CUBIC)
prewhitened = facenet.prewhiten(resized)
faces.append(getEmbedding(prewhitened))
return faces
def getEmbedding(resized):
reshaped = resized.reshape(-1,input_image_size,input_image_size,3)
feed_dict = {images_placeholder: reshaped, phase_train_placeholder: False}
embedding = sess.run(embeddings, feed_dict=feed_dict)
return embedding
def compare2face(img1):
print("checking")
face2 = getFace(img1)
face1 = []
with open(os.path.join(os.getcwd(),"Face_recognition","trained_knn_model.PB"), 'rb') as f:
for i in range(4):
face1.append(pickle.load(f))
names = ["x","y","z","p"]
print("verifying name")
for i in range(0,len(face1)):
if face1[i] and face2:
# calculate Euclidean distance
dist = np.sqrt(np.sum(np.square(np.subtract(face1[i], face2[0]))))
if dist <= 0.8:
return "dist: "+str(dist)+"\nhello "+names[i]
return "Person not found"
def recognizeFace(image_path):
image = cv2.imread(image_path)
response = compare2face(image)
return response
语音合成：
import io
import numpy as np
import tensorflow as tf
from .hparams import hparams
from librosa import effects
from .models import create_model
from .text import text_to_sequence
from .util import audio
class Synthesizer:
def load(self, checkpoint_path, sess, model_name='tacotron'):
print('Constructing model: %s' % model_name)
inputs = tf.placeholder(tf.int32, [1, None], 'inputs')
input_lengths = tf.placeholder(tf.int32, [1], 'input_lengths')
with tf.variable_scope('model') as scope:
self.model = create_model(model_name, hparams)
self.model.initialize(inputs, input_lengths)
self.wav_output = audio.inv_spectrogram_tensorflow(self.model.linear_outputs[0])
print('Loading checkpoint: %s' % checkpoint_path)
# self.session = tf.Session()
self.session = sess
self.session.run(tf.global_variables_initializer())
saver = tf.train.Saver()
saver.restore(self.session, checkpoint_path)
def synthesize(self, text):
cleaner_names = [x.strip() for x in hparams.cleaners.split(',')]
seq = text_to_sequence(text, cleaner_names)
feed_dict = {
self.model.inputs: [np.asarray(seq, dtype=np.int32)],
self.model.input_lengths: np.asarray([len(seq)], dtype=np.int32)
}
wav = self.session.run(self.wav_output, feed_dict=feed_dict)
wav = audio.inv_preemphasis(wav)
wav = wav[:audio.find_endpoint(wav)]
out = io.BytesIO()
audio.save_wav(wav, out)
return out.getvalue()
错误如下：
2019-11-11 21:48:04.408636: W tensorflow/core/framework/op_kernel.cc:1502] OP_REQUIRES failed at save_restore_v2_ops.cc:184 : Not found: Key onet/conv1/biases not found in checkpoint
Traceback (most recent call last):
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1356, in _do_call
return fn(*args)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1341, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1429, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: 2 root error(s) found.
(0) Not found: Key onet/conv1/biases not found in checkpoint
[[{{node save/RestoreV2}}]]
[[save/RestoreV2/_617]]
(1) Not found: Key onet/conv1/biases not found in checkpoint
[[{{node save/RestoreV2}}]]
0 successful operations.
0 derived errors ignored.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1286, in restore
{self.saver_def.filename_tensor_name: save_path})
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _do_run
run_metadata)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1370, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: 2 root error(s) found.
(0) Not found: Key onet/conv1/biases not found in checkpoint
[[node save/RestoreV2 (defined at F:\Backend\Text_To_Speech\synthesizer.py:25) ]]
[[save/RestoreV2/_617]]
(1) Not found: Key onet/conv1/biases not found in checkpoint
[[node save/RestoreV2 (defined at F:\Backend\Text_To_Speech\synthesizer.py:25) ]]
0 successful operations.
0 derived errors ignored.
Original stack trace for 'save/RestoreV2':
File "commonServer.py", line 38, in <module>
synthesizer.load(model_path,sess)
File "F:\Backend\Text_To_Speech\synthesizer.py", line 25, in load
saver = tf.train.Saver()
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 825, in __init__
self.build()
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 837, in build
self._build(self._filename, build_save=True, build_restore=True)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 875, in _build
build_restore=build_restore)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 508, in _build_internal
restore_sequentially, reshape)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 328, in _AddRestoreOps
restore_sequentially)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 575, in bulk_restore
return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 1696, in restore_v2
name=name)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 3616, in create_op
op_def=op_def)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in __init__
self._traceback = tf_stack.extract_stack()
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1296, in restore
names_to_keys = object_graph_key_mapping(save_path)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1614, in object_graph_key_mapping
object_graph_string = reader.get_tensor(trackable.OBJECT_GRAPH_PROTO_KEY)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 678, in get_tensor
return CheckpointReader_GetTensor(self, compat.as_bytes(tensor_str))
tensorflow.python.framework.errors_impl.NotFoundError: Key _CHECKPOINTABLE_OBJECT_GRAPH not found in checkpoint
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "commonServer.py", line 38, in <module>
synthesizer.load(model_path,sess)
File "F:\Backend\Text_To_Speech\synthesizer.py", line 26, in load
saver.restore(self.session, checkpoint_path)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 1302, in restore
err, "a Variable name or other graph key that is missing")
tensorflow.python.framework.errors_impl.NotFoundError: Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:
2 root error(s) found.
(0) Not found: Key onet/conv1/biases not found in checkpoint
[[node save/RestoreV2 (defined at F:\Backend\Text_To_Speech\synthesizer.py:25) ]]
[[save/RestoreV2/_617]]
(1) Not found: Key onet/conv1/biases not found in checkpoint
[[node save/RestoreV2 (defined at F:\Backend\Text_To_Speech\synthesizer.py:25) ]]
0 successful operations.
0 derived errors ignored.
Original stack trace for 'save/RestoreV2':
File "commonServer.py", line 38, in <module>
synthesizer.load(model_path,sess)
File "F:\Backend\Text_To_Speech\synthesizer.py", line 25, in load
saver = tf.train.Saver()
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 825, in __init__
self.build()
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 837, in build
self._build(self._filename, build_save=True, build_restore=True)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 875, in _build
build_restore=build_restore)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 508, in _build_internal
restore_sequentially, reshape)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 328, in _AddRestoreOps
restore_sequentially)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\training\saver.py", line 575, in bulk_restore
return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 1696, in restore_v2
name=name)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 3616, in create_op
op_def=op_def)
File "C:\Users\Jaydip Bari\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in __init__
self._traceback = tf_stack.extract_stack()
最初，我首先尝试加载face_recognition模型，然后加载TTS模型。一无所有，我尝试先加载TTS模型，然后再加载Face_recognition模型，您猜怎么着？它运行完美，没有任何错误。我不知道它是如何反向工作的。如果仍然有人知道答案，请帮助。