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| import time | |
| import streamlit as st | |
| import numpy as np | |
| from PIL import Image | |
| import urllib.request | |
| import io | |
| from utils import * | |
| # Initialize labels and model | |
| labels = gen_labels() | |
| model = model_arc() # Assuming this function initializes and returns a trained model | |
| # Streamlit UI | |
| st.markdown(''' | |
| <div style="padding-bottom: 20px; padding-top: 20px; padding-left: 5px; padding-right: 5px"> | |
| <center><h1>EcoIdentify (Test)</h1></center> | |
| </div> | |
| ''', unsafe_allow_html=True) | |
| st.markdown(''' | |
| <div> | |
| <center><h3>Please upload Waste Image to find its Category</h3></center> | |
| </div> | |
| ''', unsafe_allow_html=True) | |
| opt = st.selectbox("How do you want to upload the image for classification?", | |
| ('Please Select', 'Upload image via link', 'Upload image from device')) | |
| # Image processing based on user selection | |
| image = None | |
| if opt == 'Upload image from device': | |
| file = st.file_uploader('Select', type=['jpg', 'png', 'jpeg']) | |
| if file: | |
| try: | |
| image = Image.open(io.BytesIO(file.read())).resize((256, 256), Image.LANCZOS) | |
| except Exception as e: | |
| st.error(f"Error reading the file: {e}") | |
| elif opt == 'Upload image via link': | |
| img_url = st.text_input('Enter the Image Address') | |
| if st.button('Submit'): | |
| try: | |
| response = urllib.request.urlopen(img_url) | |
| image = Image.open(response).resize((256, 256), Image.LANCZOS) | |
| except ValueError: | |
| st.error("Please Enter a valid Image Address!") | |
| try: | |
| if image is not None: | |
| st.image(image, width = 256, caption = 'Uploaded Image') | |
| if st.button('Predict'): | |
| img = preprocess(image) | |
| model = model_arc() | |
| #model.load_weights("classify_model.h5") | |
| print("---------------img-array---------------------") | |
| print(img[np.newaxis, ...]) | |
| prediction = model.predict(img[np.newaxis, ...]) | |
| print("------------summary------------------------") | |
| print(model.summary()) | |
| print("------------------------------------") | |
| print(prediction) | |
| st.info('Hey! The uploaded image has been classified as " {} waste " '.format(labels[np.argmax(prediction[0], axis=-1)]) + ) | |
| def | |
| if img == 'paper' or 'cardboard' or 'metal' or 'glass': | |
| return(" therefore your item is recyclable. Please refer to https://www.wm.com/us/en/drop-off-locations to find a drop-off location near you.") | |
| elif img == 'plastic': | |
| return(' therefore you item may have a chance of being recyclable. Since this model has yet to recognize types of plastics, please refer to https://www.bing.com/ck/a?!&&p=c1474e95017548dfJmltdHM9MTcwMzcyMTYwMCZpZ3VpZD0xNmNjOTFiOS1hMDgwLTY5MmItMzBmNi04MmE1YTE3ODY4NDImaW5zaWQ9NTIyMA&ptn=3&ver=2&hsh=3&fclid=16cc91b9-a080-692b-30f6-82a5a1786842&psq=what+type+of+plastic+can+be+recycled&u=a1aHR0cHM6Ly93d3cucGxhc3RpY3Nmb3JjaGFuZ2Uub3JnL2Jsb2cvd2hpY2gtcGxhc3RpYy1jYW4tYmUtcmVjeWNsZWQ&ntb=1 to check if this item can be recycled.') | |
| else: | |
| return('Your item is not recyclable. Please discard it safely.') | |
| except Exception as e: | |
| st.info(e) | |
| pass |