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Update README.md

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@@ -23,19 +23,29 @@ This project is licensed under the MIT License.
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  <h1>How to use:</h1>
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  <br>
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- On inference</br>
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  ```ruby
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- import PaViT
 
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  import cv2
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- from tensorflow.keras.models import *
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- image=cv2.imread(image) #Load image
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- image=cv2.cvtColor(image, cv2.COLOR_BGR2RGB) #Convert image to RGB
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- image=cv2.resize(224, 224) #Default image size
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- model=load_model('trained_weight.h5') #Load weight
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- prediction=model.predict(image) #run inference
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- prediction=np.argmax(prediction, axis=-1) #Show highest probability class
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  <br>On Training</br>
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  ```ruby
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  model=PaViT.PaViT()
 
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  <h1>How to use:</h1>
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  <br>
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+ Import Librariese</br>
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  ```ruby
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+ !pip install huggingface_hub["tensorflow"]
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+ import matplotlib.pyplot as plt
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  import cv2
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+ from huggingface_hub import from_pretrained_keras
 
 
 
 
 
 
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  ```
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+ <h1>On inference</h1><br>
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+ ```ruby
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+ #load model
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+ model=from_pretrained_keras('Ajibola/PaViT')
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+
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+ #load image
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+ image=cv2.imread('image_path')
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+ image=cv2.resize(image, (224, 224)) #224 is the default image size
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+ image=image.image.max() #Normalize the image to [0-1]
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+ prediction=model.predict(image)
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+ prediction=np.argmax(prediction, axis=-1) #Get Highest probability class
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+
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+
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+ ```
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+
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  <br>On Training</br>
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  ```ruby
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  model=PaViT.PaViT()