I get this error --> AttributeError: 'NoneType' object has no attribute 'predict'

Question

I get this error many times.

Traceback (most recent call last):                                                        
  File "E:\AI and ML-pr\day14\test.py", line 38, in <module>
  result = loaded_model.predict(test_image)
  AttributeError: 'NoneType' object has no attribute 'predict'

I want to find out the diseases of the leaves of the plant.

my code::

# importing libraries
import numpy as np
from keras.preprocessing import image
from keras.models import Sequential
from keras.layers.core import Dense
from keras.models import model_from_json
import os
import cv2

#loading tha model

json_file=open('modell.json','r')
loaded_model_json=json_file.read()
json_file.close()
loaded_model=model_from_json(loaded_model_json)

# load weights into new model
loaded_model = loaded_model.load_weights("modell.h5")
print("Loaded model succesfully**")

label = ['Apple___Apple_scab','Apple___Black_rot','Apple___Cedar_apple_rust','Apple___healthy',     
'Blueberry___healthy','Cherry_(including_sour)___healthy','Cherry_(including_sour)___Powdery_mildew','Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot','Corn_(maize)___Common_rust_', 'Corn_(maize)___healthy','Corn_(maize)___Northern_Leaf_Blight','Grape___Black_rot','Grape___Esca_(Black_Measles)','Grape___healthy','Grape___Leaf_blight_(Isariopsis_Leaf_Spot)','Orange___Haunglongbing_(Citrus_greening)','Peach___Bacterial_spot','Peach___healthy','Pepper,_bell___Bacterial_spot','Pepper,_bell___healthy','Potato___Early_blight','Potato___healthy','Potato___Late_blight','Raspberry___healthy','Soybean___healthy','Squash___Powdery_mildew','Strawberry___healthy','Strawberry___Leaf_scorch','Tomato___Bacterial_spot','Tomato___Early_blight','Tomato___healthy','Tomato___Late_blight','Tomato___Leaf_Mold','Tomato___Septoria_leaf_spot','Tomato___Spider_mites Two-spotted_spider_mite','Tomato___Target_Spot','Tomato___Tomato_mosaic_virus','Tomato___Tomato_Yellow_Leaf_Curl_Virus']

path="E:\AI and ML-pr\day14\images_for_test\AppleCedarRust1.jpg"
test_image=image.load_img(path,target_size=(128,128))
#print(test_image)
test_image=image.img_to_array(test_image)
test_image=np.expand_dims(test_image,axis=1)
result = loaded_model.predict(test_image)
print(result)
fresult=np.max(result)
label2=label[result.argmax()]
print(label2)

please solve my problem

Answer 1

The problem appears to be the line: loaded_model = loaded_model.load_weights("modell.h5")

From the documentation for load_weights() :

When loading a weight file in TensorFlow format, returns the same status object as tf.train.Checkpoint.restore. When graph building, restore ops are run automatically as soon as the network is built (on first call for user-defined classes inheriting from Model, immediately if it is already built).

When loading weights in HDF5 format, returns None.

So it looks like changing the line to be just: loaded_model.load_weights("modell.h5") would resolve your issue.