saroz014 / plant-diseases-recognition Goto Github PK

hi , can you provide report of this project .

Loading the model you provided having accuracy around 2%.

when i click on predict button this error occurs.
please help me brother

Hi @saroz014 @bhavandar ,
I want to make an api this total application how can i make an api this application could you help me..

Thanks and Regards,
Manikantha Sekhar..

Hi Saroj,

This is a great project, how do we execute it? from terminal?

Thank you in advance!

which exact python version you used in this project

Hi @saroz014 ,
It is very helful for me i want the dataset of plant diseases which you explained in the readme.md file is their any link to download the dataset for that plant diseases

Thank and Regards,
Manikantha Sekhar.

If your python version is 3.7 or less this requirement.txt installation will work great,
Those who have python version 3.8+ will face some issues while installing Keras 1.15

For Python version 3.8+ first, install TensorFlow by

pip install tensorFlow

it will install TensorFlow version 2.5
Do these following steps in order to make the project working :

1. Replace this line graph = tf.get_default_graph() by graph= tf.compat.v1.get_default_graph() in deeplearning.py
2. Remove this import,

from keras.models import load_model

by this.

from tensorflow import keras

3. Model is loaded in deeplearning.py instead load it inside the working code

with graph.as_default():
model = tf.keras.models.load_model('AlexNetModel.hdf5')
prediction = model.predict(image_array)

4: The code is using Keras library for importing images you can now import it by Image library.

comment this line# img = image.load_img('sample_image.png', target_size=(224, 224))
comment this line# img = image.img_to_array(img)
comment this line# img = np.expand_dims(img, axis=0)
comment this line# img = img/255
comment this line# print(type(img))
comment this line# img = tf.keras.preprocessing.image.array_to_img(img_data)

Now replace those lines by these lines :

input_image=Image.open("sample_image.png")
input_image = input_image.resize((224,224), resample=Image.LANCZOS)
image_array=np.array(input_image)
image_array=image_array.astype('float32')
image_array/=255
image_array=image_array.reshape(1,224,224,3)

These steps will fix your code according to the version.