''' 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=="Tesseract"): # ocr = TesseractOCR() log.debug("TESSERACT SELECTED") imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer) # imageRedactorEngine = ImageRedactorEngine(image_analyzer_engine=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.piiEntitiesToBeRedacted == None): piiEntitiesToBeRedacted=None else: piiEntitiesToBeRedacted = payload.piiEntitiesToBeRedacted.split(',') #print("piipiiEntitiesToBeRedacted===",piiEntitiesToBeRedacted) if(payload.exclusion == None): exclusionList=[] else: exclusionList=payload.exclusion.split(",") if(payload.portfolio== None): # entities=["PERSON","LOCATION"], #print("payload103===",payload ) #print("payload.piiEntitiesToBeRedacted103==",payload.piiEntitiesToBeRedacted) if(payload.piiEntitiesToBeRedacted == None): results = imageAnalyzerEngine.analyze(image, allow_list=exclusionList) else: try: results = imageAnalyzerEngine.analyze(image,entities=piiEntitiesToBeRedacted, allow_list=exclusionList) #print("result------",results) except Exception as e: #print("error 103===",e) return 482 #print("results:",results) 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 = PIIImageAnalyze(type=result.entity_type, start=result.start, end=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=="Tesseract"): # ocr = TesseractOCR() log.debug("TESSERACT SELECTED") imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer) imageRedactorEngine = ImageRedactorEngine(image_analyzer_engine=imageAnalyzerEngine) 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.piiEntitiesToBeRedacted == None): piiEntitiesToBeRedacted=None else: piiEntitiesToBeRedacted = payload.piiEntitiesToBeRedacted.split(',') #print("piipiiEntitiesToBeRedacted===",piiEntitiesToBeRedacted) if(payload.exclusion == None): exclusionList=[] else: exclusionList=payload.exclusion.split(",") if(payload.portfolio== None): if(payload.piiEntitiesToBeRedacted == None): redacted_image = imageRedactorEngine.redact(image, (255, 192, 203), allow_list=exclusionList) try: redacted_image = imageRedactorEngine.redact(image, (255, 192, 203),entities=piiEntitiesToBeRedacted, allow_list=exclusionList) #print("result------",redacted_image) except Exception as e: #print("error 103===",e) return 482 #print("results:",redacted_image) 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=="Tesseract"): # ocr = TesseractOCR() log.debug("TESSERACT SELECTED") imageAnalyzerEngine = ImageAnalyzerEngine(analyzer_engine=analyzer) encryptImageEngin=EncryptImage(image_analyzer_engine=imageAnalyzerEngine) # 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))