app.py

import cv2
import numpy as np
import streamlit as st
from PIL import Image
import urllib.request
import io
from utils import *
from google.colab.output import eval_js
from base64 import b64decode, b64encode

# 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)

# Function to take a photo using the webcam
def take_photo(filename='photo.jpg', quality=
 0.8):
  js = Javascript('''
    async function takePhoto(quality) {
      const div = document.createElement('div');
      const capture = document.createElement('button');
      capture.textContent = 'Capture';
      div.appendChild(capture);

      const video = document.createElement('video');
      video.style.display = 'block';
      const stream = await navigator.mediaDevices.getUserMedia({ video: true });

      document.body.appendChild(div);
      div.appendChild(video);
      video.srcObject = stream;
      await video.play();

      // Resize the output to fit the video element.
      google.colab.output.setIframeHeight(document.documentElement.scrollHeight, true);

      // Wait for Capture to be clicked.
      await new Promise((resolve) => capture.onclick = resolve);

      const canvas = document.createElement('canvas');
      canvas.width = video.videoWidth;
      canvas.height = video.videoHeight;
      canvas.getContext('2d').drawImage(video, 0, 0);
      stream.getVideoTracks()[0].stop();
      div.remove();
      return canvas.toDataURL('image/jpeg', quality);
    }
  ''')
  display(js)
  data = eval_js('takePhoto({})'.format(quality))
  binary = b64decode(data.split(',')[1])
  with open(filename, 'wb') as f:
    f.write(binary)
  return filename
   

opt = st.selectbox("How do you want to upload the image for classification?",
          ('Please Select', 'Upload image via link', 'Upload image from device', 'Capture a picture'))

# 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 = cv2.imread(file)
      image = cv2.resize(image, (256, 256))
    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 = cv2.imread(io.BytesIO(response.read()))
      image = cv2.resize(image, (256, 256))
    except ValueError:
      st.error("Please Enter a valid Image Address!")

elif opt == 'Capture a picture':
  take_photo()

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 message(img):
        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.')

      st.info(message(labels[np.argmax(prediction[0], axis=-1)]))

except Exception as e:
  st.info(e)
  pass