NameError: name 'BERT_MODEL' is not defined

[rsingh888]

In the jupyter notebook BERT_MODEL is not defined. Can someone help me defining BERT_MODEL

[yashwantreddy]

Can confirm - having trouble identifying "BERT_MODEL" in

import pandas as pd import formatter as fm df = pd.read_csv(BERT_MODEL) preprocess_input, test_data = fm(df)

[Arsal96]

Issue regarding"NameError: name 'BERT_MODEL' is not defined"

[iamnamananand996]

import pandas as pd import formatter as fm df = pd.read_csv(BERT_MODEL) preprocess_input, test_data = fm(df)

df = pd.read_csv(BERT_MODEL)

where is this BERT_MODEL can anybody help me in that

[patalbansishashank]

Please help

NameError Traceback (most recent call last)

in () 1 import pandas as pd 2 import formatter as fm ----> 3 df = pd.read_csv(BERT_MODEL) 4 preprocess_input, test_data = fm(df) NameError: name 'BERT_MODEL' is not defined

[jamalavedra]

Same here, I got the NameError: name 'BERT_MODEL' is not defined as well. The issue is, how to u correclty import the labelled image library from Kaggle as a .csv file insted of as a bunch of stand alone images... only clue on that? cheers

[elchinon]

Same problem here, any insights on how to fix this? Thank you.

[nimitsolanki]

Not working with the standard approach -

import pandas as pd df = pd.read_csv('/content/chest-xray-pneumonia.zip', compression='zip', header=0, sep=',', quotechar='"')

@llSourcell , could you please update the value of BERT_MODEL?

[Darpan9o1]

This cell might not be required as 'preprocess_input' value is already included in the dependencies.

I just unzipped the input file and replace the source path in the model train like below and its running fine.

train_generator=train_datagen.flow_from_directory('/content/chest_xray', target_size=(224,224), color_mode='rgb', batch_size=32, class_mode='categorical', shuffle=True)

[nimitsolanki]

This cell might not be required as 'preprocess_input' value is already included in the dependencies.

I just unzipped the input file and replace the source path in the model train like below and its running fine.

train_generator=train_datagen.flow_from_directory('/content/chest_xray', target_size=(224,224), color_mode='rgb', batch_size=32, class_mode='categorical', shuffle=True)

Thanks! After unzipping applying train_generator, it's not able to get images, Found 0 images belonging to 0 classes.

AttributeError: 'ProgbarLogger' object has no attribute 'log_values'

---

Unzipping snippet: import zipfile with zipfile.ZipFile('/content/chest-xray-pneumonia.zip','r') as zip_ref: zip_ref.extractall('/content/chest_xray')

Could you please help!

[Darpan9o1]

The main file containing data chest_xray.zip is inside chest-xray-pneumonia.zip so you might have to zip again. You can browse through the file structure on the left in colab.

[DenisSouth]

https://github.com/DenisSouth/xray-pneumonia-detection I fix the issue, train the model, and made function for use trained network Please check the link

[nimitsolanki]

https://github.com/DenisSouth/xray-pneumonia-detection I fix the issue, train the model, and made function for use trained network Please check the link

404 page not found!

[DenisSouth]

https://github.com/DenisSouth/xray-pneumonia-detection I fix the issue, train the model, and made function for use trained network Please check the link

404 page not found!

i made it public, check it

[menzi101]

https://github.com/menzi101/gitToets/blob/master/Olorun.ipynb

A Super Dirty fix to the error.

[abisekk001]

model = ResNet50(weights= 'Puenomonia.h5')

ValueError: You are trying to load a weight file containing 58 layers into a model with 107 layers.

plzz anyone help me...

[DenisSouth]

Just use notebook from my fork

[NamanMakkar]

What is the maximum validation accuracy and the max test accuracy that you guys get ?

[aserravalle]

The main file containing data chest_xray.zip is inside chest-xray-pneumonia.zip so you might have to zip again. You can browse through the file structure on the left in colab.

You don't have to unzip gain, just reference that in the 'Train Data' cell