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'''
MIT license https://opensource.org/licenses/MIT Copyright 2024 Infosys Ltd
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
'''
import io, base64
from PIL import Image
from privacy.service.easy import EasyOCR
from privacy.service.azureComputerVision import ComputerVision
# from privacy.dao.TelemetryFlagDb import TelemetryFlag
from privacy.mappers.mappers import *
from privacy.util.encrypt import EncryptImage
from typing import List
from privacy.constants.local_constants import (DELTED_SUCCESS_MESSAGE)
from privacy.config.logger import CustomLogger
#import zipfile
from zipfile import ZipFile,is_zipfile
from dotenv import load_dotenv
from privacy.config.logger import request_id_var
load_dotenv()
import numpy as np
import cv2
# from privacy.util.flair_recognizer import FlairRecognizer
log = CustomLogger()
import time
import pytesseract
from scipy import ndimage
from PIL import Image as im
from privacy.util.special_recognizers.DataListRecognizer import DataListRecognizer
# global error_dict
from privacy.service.__init__ import *
from privacy.service.api_req import ApiCall
class ImageRotation:
def float_convertor(x):
if x.isdigit():
out= float(x)
else:
out= x
return out
def getAngle(image):
k = pytesseract.image_to_osd(image)
out = {i.split(":")[0]: ImageRotation.float_convertor(i.split(":")[-1].strip()) for i in k.rstrip().split("\n")}
return out["Rotate"]
def rotateImage(image,preAngle=0):
angle=0
# t=time.time()
if(preAngle==0):
angle=ImageRotation.getAngle(image)
# print("angle:",time.time()-t)
if(preAngle==angle):
return (image,angle)
img_rotated = ndimage.rotate(image, preAngle-angle)
image = im.fromarray(img_rotated)
return (image,angle)
class ImagePrivacy:
def image_analyze(payload):
error_dict[request_id_var.get()]=[]
try:
log.debug("Entering in image_analyze function")
payload=AttributeDict(payload)
image = Image.open(payload.image.file)
# analyzer,registry=ConfModle.getAnalyzerEngin("en_core_web_lg")
angle=0
if(payload.rotationFlag):
image,angle=ImageRotation.rotateImage(image)
ocr=None
global imageAnalyzerEngine
if(payload.easyocr=="EasyOcr"):
ocr=EasyOCR()
EasyOCR.setMag(payload.mag_ratio)
tt=time.time()
imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer,ocr=ocr)
# print(time.time()-tt)
if(payload.easyocr=="ComputerVision"):
ocr=ComputerVision()
# EasyOCR.setMag(payload.mag_ratio)
imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer,ocr=ocr)
# imageRedactorEngine = ImageRedactorEngine(image_analyzer_engine=imageAnalyzerEngine)
log.debug("payload="+str(payload))
if(payload.exclusion == None):
exclusionList=[]
else:
exclusionList=payload.exclusion.split(",")
if(payload.portfolio== None):
results = imageAnalyzerEngine.analyze(image, allow_list=exclusionList)
else:
result=[]
preEntity=[]
response_value=ApiCall.request(payload)
if(response_value==None):
return None
if(response_value==404):
# print( response_value)
return response_value
entityType,datalist,preEntity=response_value
# entityType,datalist,preEntity=ApiCall.request(payload)
# preEntity=["PERSON"]
for d in range(len(datalist)):
record=ApiCall.getRecord(entityType[d])
record=AttributeDict(record)
# log.debug("Record ======"+str(record))
if(record.RecogType=="Data"):
dataRecog=(DataListRecognizer(terms=datalist[d],entitie=[entityType[d]]))
registry.add_recognizer(dataRecog)
# log.debug("++++++"+str(entityType[d]))
# results = engine.analyze(image,entities=[entityType[d]])
# result.extend(results)
elif(record.RecogType=="Pattern" and record.isPreDefined=="No"):
contextObj=record.Context.split(',')
pattern="|".join(datalist[d])
log.debug("pattern="+str(pattern))
patternObj = Pattern(name=entityType[d],
regex=pattern,
score=record.Score)
patternRecog = PatternRecognizer(supported_entity=entityType[d],
patterns=[patternObj],context=contextObj)
registry.add_recognizer(patternRecog)
# log.debug("==========="+str(entityType[d]))
# results = engine.analyze(image,entities=[entityType[d]])
# result.extend(results)
results = imageAnalyzerEngine.analyze(image,entities=entityType+preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
result.extend(results)
# results = PrivacyService.__analyze(text=payload.inputText,accName=accMasterid.accMasterId)
# if(len(preEntity)>0):
# results = imageAnalyzerEngine.analyze(image,entities=preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# preEntity.clear()
# result.extend(results)
results=result
#log.debug(f"results: {results}")
list_PIIEntity = []
for result in results:
log.debug(f"result: {result}")
obj_PIIEntity = PIIEntity(type=result.entity_type,
beginOffset=result.start,
endOffset=result.end,
score=result.score)
log.debug(f"obj_PIIEntity: {obj_PIIEntity}")
list_PIIEntity.append(obj_PIIEntity)
del obj_PIIEntity
log.debug(f"list_PIIEntity: {list_PIIEntity}")
objPIIAnalyzeResponse = PIIAnalyzeResponse
objPIIAnalyzeResponse.PIIEntities = list_PIIEntity
log.debug("Returning from image_analyze function")
# ApiCall.encryptionList.clear()
return objPIIAnalyzeResponse
except Exception as e:
log.error(str(e))
log.error("Line No:"+str(e.__traceback__.tb_lineno))
log.error(str(e.__traceback__.tb_frame))
error_dict[request_id_var.get()].append({"UUID":request_id_var.get(),"function":"imageAnalyzeFunction","msg":str(e.__class__.__name__),"description":str(e)+"Line No:"+str(e.__traceback__.tb_lineno)})
raise Exception(e)
def temp(payload):
engine = ImageAnalyzerEngine()
image = Image.open(payload.file)
results = engine.analyze(image)
#log.debug(f"results: {results}")
list_PIIEntity = []
for result in results:
log.debug(f"result: {result}")
list_PIIEntity.append(result.entity_type)
return list_PIIEntity
def image_anonymize(payload):
log.debug("Entering in image_anonymize function")
error_dict[request_id_var.get()]=[]
try:
payload=AttributeDict(payload)
# analyzer,registry=ConfModle.getAnalyzerEngin("en_core_web_lg")
ocr=None
global imageRedactorEngine
if(payload.easyocr=="EasyOcr"):
ocr=EasyOCR()
EasyOCR.setMag(payload.mag_ratio)
imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer,ocr=ocr)
imageRedactorEngine = ImageRedactorEngine(image_analyzer_engine=imageAnalyzerEngine)
if(payload.easyocr=="ComputerVision"):
ocr=ComputerVision()
# EasyOCR.setMag(payload.mag_ratio)
imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer,ocr=ocr)
imageRedactorEngine = ImageRedactorEngine(image_analyzer_engine=imageAnalyzerEngine)
# engine = ImageRedactorEngine()
payload=AttributeDict(payload)
image = Image.open(payload.image.file)
angle=0
if(payload.rotationFlag):
image,angle=ImageRotation.rotateImage(image)
# registry.load_predefined_recognizers()
# log.debug("payload.image.file====="+str(payload.image.file))
if(payload.exclusion == None):
exclusionList=[]
else:
exclusionList=payload.exclusion.split(",")
if(payload.portfolio== None):
redacted_image = imageRedactorEngine.redact(image, (255, 192, 203), allow_list=exclusionList)
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
else:
result=[]
preEntity=[]
response_value=ApiCall.request(payload)
if(response_value==None):
return None
if(response_value==404):
# print( response_value)
return response_value
entityType,datalist,preEntity=response_value
# entityType,datalist,preEntity=ApiCall.request(payload)
for d in range(len(datalist)):
record=ApiCall.getRecord(entityType[d])
record=AttributeDict(record)
# log.debug("Record=="+str(record))
if(record.RecogType=="Data"):
dataRecog=(DataListRecognizer(terms=datalist[d],entitie=[entityType[d]]))
registry.add_recognizer(dataRecog)
# log.debug("++++++"+str(entityType[d]))
# results = engine.analyze(image,entities=[entityType[d]])
# redacted_image = engine.redact(image, (255, 192, 203),entities=[entityType[d]])
# processed_image_stream = io.BytesIO()
# redacted_image.save(processed_image_stream, format='PNG')
elif(record.RecogType=="Pattern" and record.isPreDefined=="No"):
contextObj=record.Context.split(',')
pattern="|".join(datalist[d])
log.debug("pattern="+str(pattern))
patternObj = Pattern(name=entityType[d],
regex=pattern,
score=record.Score)
patternRecog = PatternRecognizer(supported_entity=entityType[d],
patterns=[patternObj],context=contextObj)
registry.add_recognizer(patternRecog)
# log.debug("=="+str(entityType[d]))
# results = engine.analyze(image,entities=[entityType[d]])
redacted_image = imageRedactorEngine.redact(image, (255, 192, 203),entities=entityType+preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# log.debug("redacted_image=="+str(redacted_image))
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
# log.debug("redacted_image="+str(redacted_image))
image=redacted_image
# results = PrivacyService.__analyze(text=payload.inputText,accName=accMasterid.accMasterId)
# if(len(preEntity)>0):
# redacted_image = imageRedactorEngine.redact(image, (255, 192, 203),entities=preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# processed_image_stream = io.BytesIO()
# redacted_image.save(processed_image_stream, format='PNG')
# preEntity.clear()
if(angle!=0 and payload.rotationFlag==True):
redacted_image,angle=ImageRotation.rotateImage(redacted_image,angle)
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
# redacted_image.show()
# redacted_image = engine.redact(image, (255, 192, 203),entities=preEntity)
# processed_image_stream = io.BytesIO()
# redacted_image.save(processed_image_stream, format='PNG')
processed_image_bytes = processed_image_stream.getvalue()
base64_encoded_image=base64.b64encode(processed_image_bytes)
# saveImage.saveImg(base64_encoded_image)
saveImage.saveImg(base64_encoded_image)
log.debug("Returning from image_anonymize function")
# ApiCall.encryptionList.clear()
return base64_encoded_image
except Exception as e:
log.error(str(e))
log.error("Line No:"+str(e.__traceback__.tb_lineno))
log.error(str(e.__traceback__.tb_frame))
error_dict[request_id_var.get()].append({"UUID":request_id_var.get(),"function":"imageAnonimyzeFunction","msg":str(e.__class__.__name__),"description":str(e)+"Line No:"+str(e.__traceback__.tb_lineno)})
raise Exception(e)
async def image_masking(main_image,template_image):
template_gray = cv2.cvtColor(template_image, cv2.COLOR_BGR2GRAY)
# Threshold the template image to create a binary mask
_, template_mask = cv2.threshold(template_gray, 1, 255, cv2.THRESH_BINARY)
# Perform template matching
result = cv2.matchTemplate(main_image, template_image, cv2.TM_CCOEFF_NORMED)
_, max_val, _, max_loc = cv2.minMaxLoc(result)
# Get the dimensions of the template image
template_height, template_width = template_image.shape[:2]
# Create a mask with the same size as the main image
mask = np.zeros(main_image.shape[:2], dtype=np.uint8)
# Set the region of interest (ROI) in the mask based on the template location
mask[max_loc[1]:max_loc[1] + template_height, max_loc[0]:max_loc[0] + template_width] = 255
# Apply the mask to the main image
result_with_mask = cv2.bitwise_and(main_image, main_image, mask=cv2.bitwise_not(mask))
return result_with_mask
def zipimage_anonymize(payload): #$$$$$$$$$$$$
result=[]
in_memory_file=io.BytesIO(payload.file.read())
engine = ImageRedactorEngine()
log.debug("=="+str(is_zipfile(payload.file)))
with ZipFile(in_memory_file, 'r') as zObject:
for file_name in zObject.namelist():
log.debug(zObject.namelist())
log.debug("=="+str(type(zObject)))
file_data=zObject.read(file_name)
image=Image.open(io.BytesIO(file_data))
redacted_image = engine.redact(image, (255, 192, 203))
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
processed_image_bytes = processed_image_stream.getvalue()
base64_encoded_image=base64.b64encode(processed_image_bytes)
result.append(base64_encoded_image)
return result
def image_verify(payload):
error_dict[request_id_var.get()]=[]
log.debug("Entering in image_verify function")
try:
# analyzer,registry=ConfModle.getAnalyzerEngin("en_core_web_lg")
# engine1 = ImageAnalyzerEngine(analyzer_engine=analyzer)
# imagePiiVerifyEngine = ImagePiiVerifyEngine(image_analyzer_engine=imageAnalyzerEngine)
# enginex=EncryptImage(image_analyzer_engine=engine1)
global imagePiiVerifyEngine
payload=AttributeDict(payload)
image = Image.open(payload.image.file)
# registry.load_predefined_recognizers()
if(payload.exclusion == None):
exclusionList=[]
else:
exclusionList=payload.exclusion.split(",")
if(payload.portfolio== None):
verify_image = imagePiiVerifyEngine.verify(image, allow_list=exclusionList)
processed_image_stream = io.BytesIO()
verify_image.save(processed_image_stream, format='PNG')
else:
result=[]
preEntity=[]
response_value=ApiCall.request(payload)
if(response_value==None):
return None
if(response_value==404):
# print( response_value)
return response_value
entityType,datalist,preEntity=response_value
# Al=ApiCall.encryptionList
for d in range(len(datalist)):
record=ApiCall.getRecord(entityType[d])
record=AttributeDict(record)
if(record.RecogType=="Data"):
dataRecog=(DataListRecognizer(terms=datalist[d],entitie=[entityType[d]]))
registry.add_recognizer(dataRecog)
elif(record.RecogType=="Pattern" and record.isPreDefined=="No"):
contextObj=record.Context.split(',')
pattern="|".join(datalist[d])
log.debug("pattern="+str(pattern))
patternObj = Pattern(name=entityType[d],
regex=pattern,
score=record.Score)
patternRecog = PatternRecognizer(supported_entity=entityType[d],
patterns=[patternObj],context=contextObj)
registry.add_recognizer(patternRecog)
verify_image = imagePiiVerifyEngine.verify(image,entities=entityType+preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# verify_image = enginex.encrypt(image,encryptionList=Al,entities=[entityType[d]], allow_list=exclusionList)
processed_image_stream = io.BytesIO()
verify_image.save(processed_image_stream, format='PNG')
# log.debug("redacted_image="+str(redacted_image))
image=verify_image
# results = PrivacyService.__analyze(text=payload.inputText,accName=accMasterid.accMasterId)
# if(len(preEntity)>0):
# verify_image = imagePiiVerifyEngine.verify(image,entities=preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# # verify_image = enginex.encrypt(image,encryptionList=Al,entities=preEntity, allow_list=exclusionList)
# processed_image_stream = io.BytesIO()
# verify_image.save(processed_image_stream, format='PNG')
# preEntity.clear()
processed_image_bytes = processed_image_stream.getvalue()
base64_encoded_image=base64.b64encode(processed_image_bytes)
saveImage.saveImg(base64_encoded_image)
log.debug("Returning from image_verify function")
# ApiCall.encryptionList.clear()
return base64_encoded_image
except Exception as e:
log.error(str(e))
log.error("Line No:"+str(e.__traceback__.tb_lineno))
log.error(str(e.__traceback__.tb_frame))
error_dict[request_id_var.get()].append({"UUID":request_id_var.get(),"function":"imageVeryFunction","msg":str(e.__class__.__name__),"description":str(e)+"Line No:"+str(e.__traceback__.tb_lineno)})
raise Exception(e)
def imageEncryption(payload):
error_dict[request_id_var.get()]=[]
log.debug("Entering in imageEncryption function")
try:
payload=AttributeDict(payload)
EncryptImage.entity.clear()
# analyzer,registry=ConfModle.getAnalyzerEngin("en_core_web_lg")
ocr=None
global encryptImageEngin
if(payload.easyocr=="EasyOcr"):
ocr=EasyOCR()
EasyOCR.setMag(payload.mag_ratio)
imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer,ocr=ocr)
encryptImageEngin=EncryptImage(image_analyzer_engine=imageAnalyzerEngine) #
if(payload.easyocr=="ComputerVision"):
ocr=ComputerVision()
# EasyOCR.setMag(payload.mag_ratio)
imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer,ocr=ocr)
encryptImageEngin=EncryptImage(image_analyzer_engine=imageAnalyzerEngine)
# engine = ImageRedactorEngine(image_analyzer_engine=engine1)
# engine = ImageRedactorEngine()
payload=AttributeDict(payload)
image = Image.open(payload.image.file)
angle=0
if(payload.rotationFlag):
image,angle=ImageRotation.rotateImage(image)
# registry.load_predefined_recognizers()
# log.debug("payload.image.file====="+str(payload.image.file))
encryptMapper=[]
if(payload.exclusion == None):
exclusionList=[]
else:
exclusionList=payload.exclusion.split(",")
encryptImageEngin.getText(image)
if(payload.portfolio== None):
# redacted_image = engine.redact(image, (255, 192, 203), allow_list=exclusionList)
redacted_image = encryptImageEngin.imageAnonimyze(image, (255, 192, 203), allow_list=exclusionList)
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
else:
result=[]
preEntity=[]
response_value=ApiCall.request(payload)
# encryptionList=ApiCall.encryptionList
if(response_value==None):
return None
if(response_value==404):
# print( response_value)
return response_value
encryptionList=admin_par[request_id_var.get()]["encryptionList"]
entityType,datalist,preEntity=response_value
# entityType,datalist,preEntity=ApiCall.request(payload)
for d in range(len(datalist)):
record=ApiCall.getRecord(entityType[d])
record=AttributeDict(record)
# log.debug("Record=="+str(record))
if(record.RecogType=="Data"):
dataRecog=(DataListRecognizer(terms=datalist[d],entitie=[entityType[d]]))
registry.add_recognizer(dataRecog)
# log.debug("++++++"+str(entityType[d]))
# results = engine.analyze(image,entities=[entityType[d]])
# redacted_image = engine.redact(image, (255, 192, 203),entities=[entityType[d]])
# processed_image_stream = io.BytesIO()
# redacted_image.save(processed_image_stream, format='PNG')
elif(record.RecogType=="Pattern" and record.isPreDefined=="No"):
contextObj=record.Context.split(',')
pattern="|".join(datalist[d])
log.debug("pattern="+str(pattern))
patternObj = Pattern(name=entityType[d],
regex=pattern,
score=record.Score)
patternRecog = PatternRecognizer(supported_entity=entityType[d],
patterns=[patternObj],context=contextObj)
registry.add_recognizer(patternRecog)
# log.debug("=="+str(entityType[d]))
# results = engine.analyze(image,entities=[entityType[d]])
redacted_image = encryptImageEngin.imageAnonimyze(image, (255, 192, 203),encryptionList=encryptionList,entities=entityType+preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# log.debug("redacted_image=="+str(redacted_image))
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
# log.debug("redacted_image="+str(redacted_image))
image=redacted_image
# results = PrivacyService.__analyze(text=payload.inputText,accName=accMasterid.accMasterId)
# if(len(preEntity)>0):
# redacted_image = encryptImageEngin.imageAnonimyze(image, (255, 192, 203),encryptionList=encryptionList,entities=preEntity, allow_list=exclusionList,score_threshold=admin_par[request_id_var.get()]["scoreTreshold"])
# processed_image_stream = io.BytesIO()
# redacted_image.save(processed_image_stream, format='PNG')
# preEntity.clear()
EncryptImage.dis()
res=encryptImageEngin.encrypt(redacted_image,encryptionList=encryptionList)
redacted_image=res[0]
encryptMapper=res[1]
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
if(angle!=0 and payload.rotationFlag==True):
redacted_image,angle=ImageRotation.rotateImage(redacted_image,angle)
processed_image_stream = io.BytesIO()
redacted_image.save(processed_image_stream, format='PNG')
# redacted_image = engine.redact(image, (255, 192, 203),entities=preEntity)
# processed_image_stream = io.BytesIO()
# redacted_image.save(processed_image_stream, format='PNG')
processed_image_bytes = processed_image_stream.getvalue()
base64_encoded_image=base64.b64encode(processed_image_bytes)
# saveImage.saveImg(base64_encoded_image)
saveImage.saveImg(base64_encoded_image)
obj={"map":encryptMapper,"img":base64_encoded_image}
log.debug("Returning from imageEncryption function")
# ApiCall.encryptionList.clear()
return obj
except Exception as e:
log.error(str(e))
log.error("Line No:"+str(e.__traceback__.tb_lineno))
log.error(str(e.__traceback__.tb_frame))
error_dict[request_id_var.get()].append({"UUID":request_id_var.get(),"function":"imageHashifyFunction","msg":str(e.__class__.__name__),"description":str(e)+"Line No:"+str(e.__traceback__.tb_lineno)})
raise Exception(e)
class saveImage:
def saveImg(img_data):
with open("imageToSave.png", "wb") as fh:
fh.write(base64.decodebytes(img_data)) |