| import streamlit as st |
| from tensorflow.keras.models import load_model |
| import numpy as np |
| from PIL import Image |
| import cv2 |
| from tensorflow.keras.preprocessing.image import img_to_array, load_img |
|
|
| @st.cache_data() |
| def load(): |
| model_path = "best_model.h5" |
| model = load_model(model_path, compile=False) |
| return model |
|
|
| |
| model = load() |
|
|
|
|
| def predict(upload): |
|
|
| img = Image.open(upload) |
| img = np.asarray(img) |
| img_resize = cv2.resize(img, (224, 224)) |
| img_resize = np.expand_dims(img_resize, axis=0) |
| pred = model.predict(img_resize) |
|
|
| rec = pred[0][0] |
|
|
| return rec |
|
|
|
|
|
|
|
|
| st.title("Poubelle Intelligente") |
|
|
| upload = st.file_uploader("Chargez l'image de votre objet", |
| type=['png', 'jpeg', 'jpg']) |
|
|
| c1, c2 = st.columns(2) |
|
|
| if upload: |
| rec = predict(upload) |
| prob_recyclable = rec * 100 |
| prob_organic = (1-rec)*100 |
|
|
| c1.image(Image.open(upload)) |
| if prob_recyclable > 50: |
| c2.write(f"Je suis certain à {prob_recyclable:.2f} % que l'objet est recyclable") |
| else: |
| c2.write(f"Je suis certain à {prob_organic:.2f} % que l'objet n'est pas recyclable") |
|
|
| |
|
|
