Spaces:
Running
Running
Vishnu Raja
commited on
Commit
·
58bd1b2
1
Parent(s):
8ba5e32
Add application file
Browse files
app.py
ADDED
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import time
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import streamlit as st
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import numpy as np
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from PIL import Image
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import urllib.request
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from utils import *
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import requests
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labels = gen_labels()
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html_temp = '''
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<div style="padding-bottom: 20px; padding-top: 20px; padding-left: 5px; padding-right: 5px">
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<center><h1>Garbage Segregation</h1></center>
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</div>
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'''
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st.markdown(html_temp, unsafe_allow_html=True)
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html_temp = '''
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<div>
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<h2></h2>
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<center><h3>Please upload Waste Image to find its Category</h3></center>
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</div>
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'''
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st.markdown(html_temp, unsafe_allow_html=True)
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opt = st.selectbox("How do you want to upload the image for classification?\n", ('Please Select', 'Upload image via link', 'Upload image from device'))
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image = None # Initialize image variable
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if opt == 'Upload image from device':
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file = st.file_uploader('Select', type=['jpg', 'png', 'jpeg'])
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if file is not None:
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image = Image.open(file).resize((256, 256), Image.LANCZOS)
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elif opt == 'Upload image via link':
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try:
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img = st.text_input('Enter the Image Address')
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image = Image.open(urllib.request.urlopen(img)).resize((256, 256), Image.LANCZOS)
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except:
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if st.button('Submit'):
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show = st.error("Please Enter a valid Image Address!")
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time.sleep(4)
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show.empty()
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try:
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if image is not None:
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st.image(image, width=256, caption='Uploaded Image')
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if st.button('Predict'):
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img = preprocess(image)
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model = model_arc()
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image_url = "https://drive.google.com/file/d/1jc_gp8qR8t6e8z8WOA_K-SqfurN7Z8vn/view?usp=sharing"
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r = requests.get(image_url)
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# Save the content of the response to a temporary file
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with open("temp_weights.h5", "wb") as f:
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f.write(r.content)
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# Load the weights from the temporary file
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model.load_weights("temp_weights.h5")
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prediction = model.predict(img)
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st.info('Hey! The uploaded image has been classified as "{} waste" '.format(labels[np.argmax(prediction)]))
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except Exception as e:
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st.info(str(e))
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