无法将Google Colab中制作的.h5文件加载到Jupyter Notebook [英] Unable to load .h5 file made in Google Colab to Jupyter Notebook
问题描述
我尝试了面罩检测和警报系统的代码，但与此同时却遇到了错误.我在Google Collaboratory中训练了该模型，并在Jupyter Notebook中运行了以下代码.代码如下:
I tried a code for Face mask detect and alert system and I am getting an error regarding the same. I trained the model in Google Collaboratory and ran the following code in Jupyter Notebook. The code is as follows:
# Import necessary libraries
from keras.models import load_model
import cv2
import numpy as np
import tkinter
from tkinter import messagebox
import smtplib
# Initialize Tkinter
root = tkinter.Tk()
root.withdraw()
#Load trained deep learning model
model = load_model('face_mask_detection_alert_system.h5')
#Classifier to detect face
face_det_classifier=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# Capture Video
vid_source=cv2.VideoCapture(0)
# Dictionaries containing details of Wearing Mask and Color of rectangle around face. If wearing mask
then color would be
# green and if not wearing mask then color of rectangle around face would be red
text_dict={0:'Mask ON',1:'No Mask'}
rect_color_dict={0:(0,255,0),1:(0,0,255)}
SUBJECT = "Subject"
TEXT = "One Visitor violated Face Mask Policy. See in the camera to recognize user. A Person has been
detected without a face mask in the Hotel Lobby Area 9. Please Alert the authorities."
# While Loop to continuously detect camera feed
while(True):
ret, img = vid_source.read()
grayscale_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = face_det_classifier.detectMultiScale(grayscale_img,1.3,5)
for (x,y,w,h) in faces:
face_img = grayscale_img[y:y+w,x:x+w]
resized_img = cv2.resize(face_img,(56,56))
normalized_img = resized_img/255.0
reshaped_img = np.reshape(normalized_img,(1,56,56,1))
result=model.predict(reshaped_img)
label=np.argmax(result,axis=1)[0]
cv2.rectangle(img,(x,y),(x+w,y+h),rect_color_dict[label],2)
cv2.rectangle(img,(x,y-40),(x+w,y),rect_color_dict[label],-1)
cv2.putText(img, text_dict[label], (x, y-10),cv2.FONT_HERSHEY_SIMPLEX,0.8,(0,0,0),2)
# If label = 1 then it means wearing No Mask and 0 means wearing Mask
if (label == 1):
# Throw a Warning Message to tell user to wear a mask if not wearing one. This will
stay
#open and No Access will be given He/She wears the mask
messagebox.showwarning("Warning","Access Denied. Please wear a Face Mask")
# Send an email to the administrator if access denied/user not wearing face mask
message = 'Subject: {}\n\n{}'.format(SUBJECT, TEXT)
mail = smtplib.SMTP('smtp.gmail.com', 587)
mail.ehlo()
mail.starttls()
mail.login('aaaa@gmail.com','bbbb@gmail.com')
mail.sendmail('aaaa@gmail.com','aaaa@gmail.com',message)
mail.close
else:
pass
break
cv2.imshow('LIVE Video Feed',img)
key=cv2.waitKey(1)
if(key==27):
break
cv2.destroyAllWindows()
source.release()
错误:
Using TensorFlow backend.
Traceback (most recent call last):
File "C:\Users\IZZY\Desktop\Dataset\facemaskalert_2.py", line 14, in <module>
model = load_model('face_mask_detection_alert_system.h5')
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\engine\saving.py", line 492, in load_wrapper
return load_function(*args, **kwargs)
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\engine\saving.py", line 584, in load_model
model = _deserialize_model(h5dict, custom_objects, compile)
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\engine\saving.py", line 274, in _deserialize_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\engine\saving.py", line 627, in model_from_config
return deserialize(config, custom_objects=custom_objects)
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\layers\__init__.py", line 168, in deserialize
printable_module_name='layer')
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\utils\generic_utils.py", line 147, in deserialize_keras_object
list(custom_objects.items())))
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\engine\sequential.py", line 301, in from_config
custom_objects=custom_objects)
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\layers\__init__.py", line 168, in deserialize
printable_module_name='layer')
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\utils\generic_utils.py", line 149, in deserialize_keras_object
return cls.from_config(config['config'])
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\engine\base_layer.py", line 1179, in from_config
return cls(**config)
File "C:\Users\IZZY\AppData\Local\Programs\Python\Python37\lib\site-
packages\keras\legacy\interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
TypeError: __init__() got an unexpected keyword argument 'ragged'
源代码: https://theaiuniversity.com/courses/face -mask-detection-alert-system/
尝试过的方法，但没有帮助:在Keras中出现了意外的关键字参数"ragged"
Methods Tried but did not help : Unexpected keyword argument 'ragged' in Keras
-h5文件 https://drive.google.com/file/d/10oHrqtrYoD2Hx0olLnnfK0qYSQLlrt3 view?usp = sharing .
推荐答案
问题似乎与此这里公认的答案是，导出的模型可能来自tf.keras，而不是直接来自keras:
As the accepted answer here mentions that the exported model may be from tf.keras and not keras directly :
"当您使用Tensorflow的模型保存模型时，请不要直接导入keras keras高级api.将所有导入更改为tensorflow.keras".
"Don't import keras directly as your model is saved with Tensorflow's keras high level api. Change all your imports to tensorflow.keras".
我的建议:
1.您应该尝试将tf.keras用于所有keras导入
1.You should try to use tf.keras for all keras imports
-
而且正如穆罕默德在答案中提到的那样，在load_model中使用
compile=False.
在colab和本地环境中检查tf和keras的版本.两个版本必须相同.
Check the version of tf and keras in colab and local environment.Both versions need to be same.
来自 Keras github 问题.
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