UjjwalVIT's picture
Upload 4 files
575adcc
raw
history blame
12.2 kB
import streamlit as st
import streamlit.components.v1 as stc
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from PIL import Image
import exifread # Extracts Meta data of images
import os
from datetime import datetime
import mutagen # Extracts Meta data of Audio
from PIL.ExifTags import TAGS, GPSTAGS
import base64
import time
from PyPDF2 import PdfReader
timestr = time.strftime("%Y%m%d-%H%M%S")
import sqlite3
details = """
Metadata is defined as the data providing information about one or more aspects of the data; it is used to summarize basic information about data which can make tracking and working with specific data easier
"""
HTML_BANNER = """
<div style="background-color:violet;padding:10px;border-radius:10px">
<h1 style="color:white;text-align:center;">MetaData Extractor App </h1>
</div>
"""
def file_download(data):
csv_file= data.to_csv()
b64=base64.b64encode(csv_file.encode()).decode()
new_filename="result_{}.csv".format(timestr)
st.markdown('### πŸ—ƒοΈ Download csv file ')
href=f'<a href="data:file/csv;base64,{b64}" download="{new_filename}"> Click Here! </a>'
st.markdown(href, unsafe_allow_html=True)
conn=sqlite3.connect('data.db')
c=conn.cursor()
def create_filestable():
c.execute('CREATE TABLE IF NOT EXISTS filestable(filename TEXT,filetype TEXT,filesize TEXT,uploadDate TIMESTAMP)')
def add_file_details():
c.execute('INSERT INTO filestable(filename, filetype, filesize, uploadDate) VALUES (?, ?, ?, ?)', (filename, filetype, filesize, uploadDate))
conn.commit()
def view_all_data():
c.execute('SELECT * FROM filestable')
data = c.fetchall()
return data
def load_image(file):
img = Image.open(file)
return img
def get_readable_time(time):
return datetime.fromtimestamp(time).strftime('%Y-%m-%d-%H:%M')
def get_exif(filename):
exif = Image.open(filename).getexif()
if exif is not None and isinstance(exif, dict):
for key, value in exif.items():
name = TAGS.get(key, value)
exif[name] = exif.pop(key)
if 'GPSInfo' in exif:
for key in exif['GPSInfo'].keys():
name = GPSTAGS.get(key,key)
exif['GPSInfo'][name] = exif['GPSInfo'].pop(key)
return exif
def metadata():
# st.title('Meta-Data Extractor App')
stc.html(HTML_BANNER)
menu=['Home','Image','Audio','Document_Files','Analytics']
choice=st.sidebar.selectbox('Menu',menu)
create_filestable()
if choice=='Home':
st.image(load_image('extraction_process.png'))
st.write(details)
col1, col2, col3 = st.columns(3)
with col1:
with st.expander("Get Image Metadata πŸ“·"):
st.info("Image Metadata")
st.markdown("πŸ“·")
st.text("Upload JPEG,JPG,PNG Images")
with col2:
with st.expander("Get Audio Metadata πŸ”‰"):
st.info("Audio Metadata")
st.markdown("πŸ”‰")
st.text("Upload Mp3,Ogg")
with col3:
with st.expander("Get Document Metadata πŸ“„πŸ“"):
st.info("Document Files Metadata")
st.markdown("πŸ“„πŸ“")
st.text("Upload PDF,Docx")
elif choice=='Image':
st.subheader('Image MetaData Extractor')
image_file = st.file_uploader("Upload Image", type=["png", "jpg", "jpeg"])
if image_file is not None:
with st.expander('File Stats'):
file_details={'Filename':image_file.name,
'Filesize':image_file.size,
'Filetype':image_file.type}
statinfo=os.stat(image_file.readable())
statdetails={
'Accessed Time': get_readable_time(statinfo.st_atime),
'Creation Time':get_readable_time(statinfo.st_ctime),
'Modified Time':get_readable_time(statinfo.st_mtime)}
full_details={
'Filename':image_file.name,
'Filesize':image_file.size,
'Filetype':image_file.type,
'Accessed Time': get_readable_time(statinfo.st_atime),
'Creation Time':get_readable_time(statinfo.st_ctime),
'Modified Time':get_readable_time(statinfo.st_mtime)
}
# st.write(full_details)
file_details_df = pd.DataFrame(
list(full_details.items()), columns=["Meta Tags", "Value"]
)
st.dataframe(file_details_df)
c1, c2 = st.columns(2)
with c1:
with st.expander("View Image"):
img = load_image(image_file)
st.image(img,width=250)
with c2:
with st.expander("Default(JPEG)"):
st.info("Using PILLOW")
img = load_image(image_file)
img_details = {
"format": img.format,
"format_desc": img.format_description,
"filename": img.filename,
"size": img.size,
"height": img.height,
"width": img.width,
"info": img.info,
}
df_img_details = pd.DataFrame(
list(img_details.items()), columns=["Meta Tags", "Value"]
)
st.dataframe(df_img_details)
c3,c4=st.columns(2)
with c3:
with st.expander('Using ExifRead Tool'):
meta_data=exifread.process_file(image_file)
# st.write(meta_data)
meta_data_df=pd.DataFrame(
list(meta_data.items()),columns=['Meta Data','Values'])
st.dataframe(meta_data_df)
with c4:
with st.expander('Image geo Coordinates'):
img_gps_details=get_exif(image_file)
latitude = img_gps_details.get('GPSLatitude')
longitude = img_gps_details.get('GPSLongitude')
try:
gps_info = img_gps_details
lat=latitude
long=longitude
except:
gps_info = "None Found"
st.write(gps_info)
st.write(lat)
st.write(long)
add_file_details(img.filename,img.format,img.size,datetime.now())
with st.expander('Download Results'):
final_df=pd.concat([file_details_df,df_img_details,meta_data_df])
st.dataframe(final_df)
file_download(final_df)
elif choice=='Audio':
st.subheader('Audio MetaData Extractor')
audio_file = st.file_uploader("Upload Audio", type=["mp3", "ogg"])
if audio_file is not None:
col1, col2 = st.columns(2)
with col1:
st.audio(audio_file.read())
with col2:
with st.expander("File Stats"):
file_details = {
"FileName": audio_file.name,
"FileSize": audio_file.size,
"FileType": audio_file.type,
}
add_file_details(audio_file.name,audio_file.type,audio_file.size,datetime.now())
st.write(file_details)
statinfo = os.stat(audio_file.readable())
stats_details = {
"Accessed_Time": get_readable_time(statinfo.st_atime),
"Creation_Time": get_readable_time(statinfo.st_ctime),
"Modified_Time": get_readable_time(statinfo.st_mtime),
}
st.write(stats_details)
file_details_combined = {
"FileName": audio_file.name,
"FileSize": audio_file.size,
"FileType": audio_file.type,
"Accessed_Time": get_readable_time(statinfo.st_atime),
"Creation_Time": get_readable_time(statinfo.st_ctime),
"Modified_Time": get_readable_time(statinfo.st_mtime),
}
df_file_details = pd.DataFrame(
list(file_details_combined.items()),
columns=["Meta Tags", "Value"],
)
st.dataframe(df_file_details)
with st.expander('Metadata using Mutagen'):
meta_data=mutagen.File(audio_file)
meta_data_dict={str(key):str(value) for key,value in meta_data.items()}
meta_data_audio_df=pd.DataFrame(
list(meta_data_dict.items()),columns=['Tag','Values'])
st.dataframe(meta_data_audio_df)
with st.expander("Download Results"):
combined_df = pd.concat([df_file_details, meta_data_audio_df])
st.dataframe(combined_df)
file_download(combined_df)
elif choice=='Document_Files':
st.subheader('Document MetaData Extractor')
text_file = st.file_uploader("Upload File", type=["PDF"])
if text_file is not None:
col1, col2 = st.columns([1, 2])
with col1:
with st.expander("File Stats"):
file_details = {
"FileName": text_file.name,
"FileSize": text_file.size,
"FileType": text_file.type,
}
add_file_details(text_file.name,text_file.type,text_file.size,datetime.now())
st.write(file_details)
statinfo = os.stat(text_file.readable())
stats_details = {
"Accessed_Time": get_readable_time(statinfo.st_atime),
"Creation_Time": get_readable_time(statinfo.st_ctime),
"Modified_Time": get_readable_time(statinfo.st_mtime),
}
st.write(stats_details)
# Combine All Details
file_details_combined = {
"FileName": text_file.name,
"FileSize": text_file.size,
"FileType": text_file.type,
"Accessed_Time": get_readable_time(statinfo.st_atime),
"Creation_Time": get_readable_time(statinfo.st_ctime),
"Modified_Time": get_readable_time(statinfo.st_mtime),
}
# Convert to DataFrame
df_file_details = pd.DataFrame(
list(file_details_combined.items()),
columns=["Meta Tags", "Value"],
)
with col2:
with st.expander("Metadata"):
pdf_file = PdfReader(text_file)
pdf_info = pdf_file.metadata
df_file_details_with_pdf = pd.DataFrame(
list(pdf_info.items()), columns=["Meta Tags", "Value"]
)
st.dataframe(df_file_details_with_pdf)
with st.expander("Download Results"):
pdf_combined_df = pd.concat([df_file_details, df_file_details_with_pdf])
st.dataframe(pdf_combined_df)
file_download(pdf_combined_df)
elif choice=='Analytics':
st.subheader('Analytics')
uploaded_files= view_all_data()
df=pd.DataFrame(uploaded_files,columns=['Filename','Filetype','Filesize','UploadDate'])
with st.expander('Monitor'):
st.success('View all uploaded files')
st.dataframe(df)
#Monitor uploads