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# -*- coding: utf-8 -*-
"""Doc_search.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1hyshr_1HJFGUVqKRjK7gfPq75lGIYjsd
"""
# !pip install gradio -q
import os
from PIL import Image
# import gradio as gr
import fitz
import glob
import pandas as pd
import numpy as np
import tsadropboxretrieval
import cv2
#from db import dropbox_upload_file,dropbox_list_files
import plotly.express as px
#########################################################################################################
# def pushToDropbox(ip1,ip2):
# df,img_list=search_docs(ip1,ip2)
# #push df first
# print('hi')
# dropbox_upload_file('.',local_file=df,dropbox_file_path='/SearchedDocs/'+ip1+'SearchSummary.csv')
# c=0
# for p in img_list: #push images gallery
# dropbox_upload_file('.',local_file=np.array(p),dropbox_file_path='/SearchedDocs/'+ip1+str(c)+'.png')
# c+=1
# return pop
#############################################################################################################
def clear():
return None,None,None,None
##################################################################################################################
# def pushAll(ip1,proj):
# df,img_list=slow_search(ip1,proj)
# #push df first
# #print('hi')
# dropbox_upload_file('.',local_file=df,dropbox_file_path='/SearchedDocs/'+ip1+'Searchedproj'+proj+'.csv')
# c=0
# for p in img_list: #push images gallery
# dropbox_upload_file('.',local_file=np.array(p),dropbox_file_path='/SearchedDocs/'+ip1+str(c)+proj+'ALL.png')
# c+=1
###########################################################################################################
def slow_search(keyword,project): #slow search in all files existing
if keyword==None:
return None,None
else:
keyword=keyword.upper()
occ=0
img_list=[]
zoom=5
mat = fitz.Matrix(zoom, zoom)
df=pd.DataFrame(columns=['Keyword','Document Name','Word Occurrence'])
#print([nela for nela in glob.glob("dropbox_plans/"+project+"*.pdf")])
Documents =tsadropboxretrieval.retrieveProjects(project)[0]
for filepdf in Documents: #loop for each file in our path
#open file
print(filepdf[0])
dbxTeam= tsadropboxretrieval.ADR_Access_DropboxTeam('user')
md, res =dbxTeam.files_download(path=filepdf[1])
data = res.content
doc=fitz.open("pdf", data)
#get no of pages in each doc
numpages=doc.page_count
occ=0 #occurrence of the word in each document
for pageno in range(0,numpages):#loop on each page to search in
contentt=doc[pageno]
matched=contentt.search_for(keyword)
# if matched:
occ+=len(matched) #collect length of matched words in the whole doc
#highlight the matched
for word in matched:
contentt.add_highlight_annot(word)
if len(matched)>0:
pix = contentt.get_pixmap(matrix = mat)
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
open_cv_image = np.array(img)
open_cv_image = cv2.cvtColor(open_cv_image, cv2.COLOR_RGB2BGR)
img_list.append(open_cv_image)
#save highlighted op
#doc.save(f'annotated{filepdf}')
#save doc name and word occ
if occ>0:
df= pd.concat([df,pd.DataFrame([[keyword,filepdf[0],occ]], columns=df.columns)], ignore_index=True)
#return word occ and unpack images
return df,img_list
#######################################################################################################
def prepare_sunburst():
try:
df=tsadropboxretrieval.GetParquetDF()
print(df)
# df=dropbox_list_files("").reset_index(drop=True)
df[['root','parent','child']]=df['path_display'].str.split('/',n=2,expand=True)
# # print(values.columns.values) #df[['root','parent','child']]
# tree=px.sunburst(df,path= ['parent', 'child'],width=700,height=600,title='Dropbox Files Hierarchy')
# tree.update_traces(textfont=dict(size=14))
# tree.write_image('imgsunburstt.png')
return df
except Exception as e:
print("can't list files "+str(e))
########################################################################################################
def search_docs(keyword,plan): #fast search in a file/couple of files
if plan==None or keyword==None:
#print(plan)
return None,None
else:
print('elsee')
keyword=keyword.upper()
occ=0
img_list=[]
zoom=5
mat = fitz.Matrix(zoom, zoom)
df=pd.DataFrame(columns=['Keyword','Document Name','Word Occurrence'])
for filepdf in plan: #glob.glob("dropbox_plans/*.pdf"): #loop for each file in our path
#open file
pdfpath,pdflink=tsadropboxretrieval.getPathtoPDF_File(nameofPDF=filepdf)
dbxTeam= tsadropboxretrieval.ADR_Access_DropboxTeam('user')
md, res =dbxTeam.files_download(path=pdfpath)
data = res.content
doc=fitz.open("pdf", data)
#get no of pages in each doc
numpages=doc.page_count
occ=0 #occurrence of the word in each document
for pageno in range(0,numpages):#loop on each page to search in
contentt=doc[pageno]
matched=contentt.search_for(keyword)
occ+=len(matched) #collect length of matched words in the whole doc
#highlight the matched
for word in matched:
print(word)
contentt.add_highlight_annot(word)
if len(matched)>0:
pix = contentt.get_pixmap(matrix = mat)
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
open_cv_image = np.array(img)
open_cv_image = cv2.cvtColor(open_cv_image, cv2.COLOR_RGB2BGR)
img_list.append(open_cv_image)
print(df)
#save highlighted op
# doc.save(f'annotated{filepdf}')
#save doc name and word occ
if occ>0:
df= pd.concat([df,pd.DataFrame([[keyword,filepdf,occ]], columns=df.columns)], ignore_index=True)
# doc.save('newwww.pdf')
return df,img_list
######################################################################################
# repo_list=os.listdir('dropbox_plans')
# pop=gr.Error('Saving to dropbox')
# #get projects name from repo list
# f=[l.split(" ")[0]+" "+l.split(" ")[1]+" "+l.split(" ")[2] for l in repo_list]
# proj_list=list(set(f))
# with gr.Blocks(css="#clear {background: rgba(200,200,0,0.2) } #search {background: orangered}") as demo:
# with gr.Tabs():
# with gr.TabItem('File Search'):
# with gr.Row():
# with gr.Column():
# ip11=gr.Textbox(label='keyword')
# ip21=gr.CheckboxGroup(repo_list,label='plan')
# b1=gr.Button('Search',elem_id="search")
# c=gr.Button('Clear',elem_id="clear")
# with gr.Column():
# df1=gr.Dataframe(label='Found files')
# op1=gr.Gallery()
# save1=gr.Button('Save to Dropbox')
# with gr.TabItem('Folder Search'):
# with gr.Row():
# with gr.Column():
# gr.Plot(prepare_sunburst())
# ip12=gr.Textbox(label='keyword')
# drop=gr.Dropdown(proj_list,label='project')
# b2=gr.Button('Search',elem_id="search")
# with gr.Column():
# df2=gr.Dataframe(label='Found files')
# op2=gr.Gallery()
# save2=gr.Button('Save to Dropbox')
# b1.click(search_docs,inputs=[ip11,ip21],outputs=[df1,op1])
# b2.click(slow_search,inputs=[ip12,drop],outputs=[df2,op2])
# save1.click(pushToDropbox,inputs=[ip11,ip21])
# save2.click(pushAll,inputs=[ip12,drop])
# c.click(clear,outputs=[ip11,ip21,df1,op1])
# demo.launch(show_error=True)
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