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import streamlit as st
import cv2
import matplotlib.pyplot as pt
import numpy as np
from PIL import Image
import io
import requests
import base64
from tempfile import NamedTemporaryFile
import logging
logging.basicConfig(filename="logfile.log",
format='%(asctime)s %(message)s',
filemode='w')
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
st.set_page_config(layout="wide")
st.title("Sketch Generator")
st.caption("Use high resolution image to get optimal results")
def verify_url(url):
try:
encoded_content = url.split(',')[1]
image_data = base64.b64decode(encoded_content)
image = Image.open(io.BytesIO(image_data))
logger.info("Valid Base64 Url")
return True, image
except Exception as e:
logger.warning("Please Enter a valid Image url"+str(e))
return False, None
def http_url_image(nk04200111):
try:
# Send an HTTP request to the URL
response = requests.get(nk04200111)
response.raise_for_status() # Raise an error for bad responses
# Open the image using PIL
image = Image.open(io.BytesIO(response.content))
logger.info("Valid http Url")
return True, image
except Exception as e:
logger.warning("Please Enter a valid Image url"+str(e))
return False, None
def process_image(url_string,validation):
try:
if validation=="http":
result,upload = http_url_image(url_string)
elif validation=="data":
result,upload = verify_url(url_string)
if result:
image_np = np.array(upload)
firstimg=cv2.cvtColor(image_np,cv2.COLOR_BGR2GRAY)
blurs=cv2.bitwise_not(firstimg)
secondimg=cv2.GaussianBlur(blurs, (21, 21),sigmaX=30, sigmaY=30)
finalimg = cv2.divide(firstimg, 255 - secondimg, scale=256)
column1,column2,column3,column4=st.columns([1,4,4,1])
with column1:
pass
with column2:
st.image(upload, caption="Original Image",width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
with column3:
if finalimg is not None:
st.image(finalimg, caption="Final Image",width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
with column4:
pass
logger.info("Image was processed successfully")
else:
st.write(f"The URL {url_string} does not contain a valid image.")
logger.warning(f"The URL {url_string} does not contain a valid image.")
return finalimg
except Exception as e:
logger.error("Exception occured while processing image: "+str(e))
def get_base64_data(data, filename):
try:
base64_data = base64.b64encode(data).decode()
download_link = f'<a href="data:application/octet-stream;base64,{base64_data}" download="{filename}">Download {filename}</a>'
logger.info("Download Link created successfully")
return download_link
except Exception as e:
logger.error("Unable to create download link"+str(e))
def save_image(finalimg):
try:
NKIMAGES=Image.fromarray(finalimg)
buffer = io.BytesIO()
NKIMAGES.save(buffer, format="PNG")
logger.info("Image was converted successfully")
# Provide a link for the user to download the processed image
st.markdown(get_base64_data(buffer.getvalue(), "Final Image.png"), unsafe_allow_html=True)
except Exception as e:
logger.error("Image conversion failed"+str(e))
def uploadfile():
try:
firstimg=None
secondimg=None
finalimg=None
val=1
selection=st.radio(" ", ["Enter Image Url:link:","Upload Image File:open_file_folder:"], index=None, disabled=False, horizontal=True, label_visibility="visible")
if selection=="Enter Image Url:link:":
cols1,cols2=st.columns([5,1])
url_string=st.text_input(" ", type="default", placeholder="Enter the image Url", label_visibility="collapsed")
if st.button("Generate"):
if url_string !="" and url_string[:4]=="http":
finalimg=process_image(url_string,"http")
save_image(finalimg)
elif url_string !=""and url_string[:4]=="data":
finalimg=process_image(url_string,"data")
save_image(finalimg)
else:
val=2
if val==2:
st.write("Enter a valid image url")
elif selection=="Upload Image File:open_file_folder:":
uploader=st.file_uploader("Upload the image here", type=None, accept_multiple_files=False, disabled=False, label_visibility="visible")
if uploader is None:
st.write("Please upload an image")
else:
upload=uploader.read()
if st.button("Generate"):
image_np = np.array(Image.open(io.BytesIO(upload)))
firstimg=cv2.cvtColor(image_np,cv2.COLOR_BGR2GRAY)
blurs=cv2.bitwise_not(firstimg)
secondimg=cv2.GaussianBlur(blurs, (21, 21),sigmaX=30, sigmaY=30)
finalimg = cv2.divide(firstimg, 255 - secondimg, scale=256)
column1,column2,column3,column4=st.columns([1,4,4,1])
with column1:
pass
with column2:
st.image(upload, caption="Original Image", width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
with column3:
if finalimg is not None:
st.image(finalimg, caption="Final Image", width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
with column4:
pass
save_image(finalimg)
logger.info("Program ran successfully")
except Exception as e:
logger.error("Error occured in uploadfile"+str(e))
if __name__=="__main__":
uploadfile()
footer="""<style>
a:link , a:visited{
color: #0000EE;
background-color: transparent;
text-decoration: underline;
}
a:hover, a:active {
color: #551A8B;
background-color: transparent;
text-decoration: underline;
}
.footer {
position: fixed;
left: 0;
bottom: 0;
width: 100%;
height:6%;
background-color: rgba(0,0,0,10);
color: white;
text-align: center;
border-radius:2px;
}
</style>
<div class="footer">
<p>Developed by <a style='display: block; text-align: center; text-decoration:none;' href="https://github.com/nandakumar1052" target="_blank">Nanda Kumar.T</a><p>
</div>
"""
st.markdown(footer,unsafe_allow_html=True)
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