File size: 820 Bytes
af4f172 34e742a af4f172 73cf922 34e742a 73cf922 34e742a 73cf922 34e742a 73cf922 34e742a 73cf922 34e742a 73cf922 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | import streamlit as st
from tensorflow.keras.models import load_model
from PIL import Image
import numpy as np
model=load_model('src/grape_disease_model.h5')
def process_image(img):
img=img.resize((170,170))
img=np.array(img)
img=img/255.0
img=np.expand_dims(img,axis=0)
return img
st.title("Üzüm yaprağı hastalıkları sınıflandırma")
st.write("Üzüm yaprağı resmini yükle ve model hastalığı tahmin etsin")
file=st.file_uploader('Bir resim sec',type=['jpg','jpeg','png'])
if file is not None:
img=Image.open(file)
st.image(img,caption='Üzüm Yaprağı')
image= process_image(img)
prediction=model.predict(image)
predicted_class=np.argmax(prediction)
class_names=['Black Rot','ESCA','Healthy','Leaf Blight']
st.write(class_names[predicted_class])
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