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af17d6f | 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 30 31 32 33 34 35 36 | import streamlit as st
import numpy as np
import pickle
import cv2
from PIL import Image
# Load model and label binarizer
@st.cache_resource
def load_model():
model = pickle.load(open('cnn_model.pkl', 'rb'))
label_binarizer = pickle.load(open('label_transform.pkl', 'rb'))
return model, label_binarizer
model, lb = load_model()
# Prediction function
def predict(image):
image = cv2.resize(image, (256, 256))
image = image.astype("float") / 255.0
image = np.expand_dims(image, axis=0)
preds = model.predict(image)
return lb.classes_[np.argmax(preds)]
# Streamlit UI
st.title("🌱 Plant Disease Detector")
uploaded_file = st.file_uploader("Upload a leaf image...", type=["jpg", "png"])
if uploaded_file is not None:
image = Image.open(uploaded_file).convert("RGB")
st.image(image, caption="Uploaded Image", use_column_width=True)
if st.button("Predict"):
img_array = np.array(image)
img_array = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
prediction = predict(img_array)
st.success(f"🔍 Prediction: {prediction}") |