def redact_(file_name, project):
import re
output_file_name = re.split('[.]', file_name)
output_file_name = output_file_name[
0] + '_redacted' + '.' + output_file_name[1]
import mimetypes
import google.cloud.dlp
import os
os.environ[
"GOOGLE_APPLICATION_CREDENTIALS"] = "C:\gcp_credentials\elaborate-howl-285701-105c2e8355a8.json"
dlp = google.cloud.dlp_v2.DlpServiceClient()
info_types = ['EMAIL_ADDRESS',
'PHONE_NUMBER'] #info types need to redacted
info_types = [{"name": info_type} for info_type in info_types]
image_redaction_configs = [] #redaction config
inspect_config = { #inspection config
"min_likelihood": 'POSSIBLE',
"info_types": info_types,
}
#filename='page0.jpg'
#project='elaborate-howl-285701'
if info_types is not None:
for info_type in info_types:
image_redaction_configs.append({"info_type": info_type})
supported_content_types = {
None: 0, # "Unspecified"
"image/jpeg": 1,
"image/bmp": 2,
"image/png": 3,
"image/svg": 4,
"text/plain": 5,
}
content_type_index = supported_content_types.get(
"application/octet-stream", 1)
with open(file_name, mode="rb") as f:
byte_item = {"type_": content_type_index, "data": f.read()}
parent = f"projects/{project}"
response = dlp.redact_image(
request={
"parent": parent,
"inspect_config": inspect_config,
"image_redaction_configs": image_redaction_configs,
"byte_item": byte_item,
})
with open(output_file_name, mode="wb") as f:
f.write(response.redacted_image)
print("Wrote {byte_count} to {filename}".format(byte_count=len(
response.redacted_image),
filename=output_file_name))
return (output_file_name)
def redact_image_all_text(
project,
filename,
output_filename,
):
"""Uses the Data Loss Prevention API to redact all text in an image.
Args:
project: The Google Cloud project id to use as a parent resource.
filename: The path to the file to inspect.
output_filename: The path to which the redacted image will be written.
Returns:
None; the response from the API is printed to the terminal.
"""
# Import the client library
import google.cloud.dlp
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Construct the image_redaction_configs, indicating to DLP that all text in
# the input image should be redacted.
image_redaction_configs = [{"redact_all_text": True}]
# Construct the byte_item, containing the file's byte data.
with open(filename, mode="rb") as f:
byte_item = {
"type": google.cloud.dlp_v2.FileType.IMAGE,
"data": f.read()
}
# Convert the project id into a full resource id.
parent = f"projects/{project}"
# Call the API.
response = dlp.redact_image(
request={
"parent": parent,
"image_redaction_configs": image_redaction_configs,
"byte_item": byte_item,
})
# Write out the results.
with open(output_filename, mode="wb") as f:
f.write(response.redacted_image)
print("Wrote {byte_count} to {filename}".format(byte_count=len(
response.redacted_image),
filename=output_filename))
def redact_image(project,
filename,
output_filename,
info_types,
min_likelihood=None,
mime_type=None):
# Import the client library
import google.cloud.dlp
# Instantiate a client.
dlp = google.cloud.dlp.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
info_types = [{'name': info_type} for info_type in info_types]
# Prepare image_redaction_configs, a list of dictionaries. Each dictionary
# contains an info_type and optionally the color used for the replacement.
# The color is omitted in this sample, so the default (black) will be used.
image_redaction_configs = []
if info_types is not None:
for info_type in info_types:
image_redaction_configs.append({'info_type': info_type})
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
'min_likelihood': min_likelihood,
'info_types': info_types,
}
# If mime_type is not specified, guess it from the filename.
if mime_type is None:
mime_guess = mimetypes.MimeTypes().guess_type(filename)
mime_type = mime_guess[0] or 'application/octet-stream'
# Select the content type index from the list of supported types.
supported_content_types = {
None: 0, # "Unspecified"
'image/jpeg': 1,
'image/bmp': 2,
'image/png': 3,
'image/svg': 4,
'text/plain': 5,
}
content_type_index = supported_content_types.get(mime_type, 0)
# Construct the byte_item, containing the file's byte data.
with open(filename, mode='rb') as f:
byte_item = {'type': content_type_index, 'data': f.read()}
# Convert the project id into a full resource id.
parent = dlp.project_path(project)
# Call the API.
response = dlp.redact_image(
parent,
inspect_config=inspect_config,
image_redaction_configs=image_redaction_configs,
byte_item=byte_item)
# Write out the results.
with open(output_filename, mode='wb') as f:
f.write(response.redacted_image)
print("Wrote {byte_count} to {filename}".format(byte_count=len(
response.redacted_image),
filename=output_filename))
def redact_image(project, filename, output_filename,
info_types, min_likelihood=None, mime_type=None):
"""Uses the Data Loss Prevention API to redact protected data in an image.
Args:
project: The Google Cloud project id to use as a parent resource.
filename: The path to the file to inspect.
output_filename: The path to which the redacted image will be written.
info_types: A list of strings representing info types to look for.
A full list of info type categories can be fetched from the API.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
mime_type: The MIME type of the file. If not specified, the type is
inferred via the Python standard library's mimetypes module.
Returns:
None; the response from the API is printed to the terminal.
"""
# Import the client library
import google.cloud.dlp
# Instantiate a client.
dlp = google.cloud.dlp.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
info_types = [{'name': info_type} for info_type in info_types]
# Prepare image_redaction_configs, a list of dictionaries. Each dictionary
# contains an info_type and optionally the color used for the replacement.
# The color is omitted in this sample, so the default (black) will be used.
image_redaction_configs = []
if info_types is not None:
for info_type in info_types:
image_redaction_configs.append({'info_type': info_type})
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
'min_likelihood': min_likelihood,
'info_types': info_types,
}
# If mime_type is not specified, guess it from the filename.
if mime_type is None:
mime_guess = mimetypes.MimeTypes().guess_type(filename)
mime_type = mime_guess[0] or 'application/octet-stream'
# Select the content type index from the list of supported types.
supported_content_types = {
None: 0, # "Unspecified"
'image/jpeg': 1,
'image/bmp': 2,
'image/png': 3,
'image/svg': 4,
'text/plain': 5,
}
content_type_index = supported_content_types.get(mime_type, 0)
# Construct the byte_item, containing the file's byte data.
with open(filename, mode='rb') as f:
byte_item = {'type': content_type_index, 'data': f.read()}
# Convert the project id into a full resource id.
parent = dlp.project_path(project)
# Call the API.
response = dlp.redact_image(
parent, inspect_config=inspect_config,
image_redaction_configs=image_redaction_configs,
byte_item=byte_item)
# Write out the results.
with open(output_filename, mode='wb') as f:
f.write(response.redacted_image)
print("Wrote {byte_count} to {filename}".format(
byte_count=len(response.redacted_image), filename=output_filename))
def redact_image(
project,
filename,
#output_filename,
info_types,
custom_regexes=None,
min_likelihood=None,
mime_type=None,
):
"""Uses the Data Loss Prevention API to redact protected data in an image.
Args:
project: The Google Cloud project id to use as a parent resource.
filename: The path to the file to inspect.
output_filename: The path to which the redacted image will be written.
info_types: A list of strings representing info types to look for.
A full list of info type categories can be fetched from the API.
min_likelihood: A string representing the minimum likelihood threshold
that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
mime_type: The MIME type of the file. If not specified, the type is
inferred via the Python standard library's mimetypes module.
Returns:
None; the response from the API is printed to the terminal.
"""
# Import the client library
import google.cloud.dlp
# Instantiate a client.
dlp = google.cloud.dlp_v2.DlpServiceClient()
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
info_types = [{"name": info_type} for info_type in info_types]
if custom_regexes is None:
custom_regexes = []
regexes = [{
"info_type": {
"name": "CUSTOM_REGEX_{}".format(i)
},
"regex": {
"pattern": "[\d]"
},
} for i, custom_regex in enumerate(custom_regexes)]
# Prepare image_redaction_configs, a list of dictionaries. Each dictionary
# contains an info_type and optionally the color used for the replacement.
# The color is omitted in this sample, so the default (black) will be used.
image_redaction_configs = []
if info_types is not None:
for info_type in info_types:
image_redaction_configs.append({"info_type": info_type})
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
"min_likelihood":
min_likelihood,
"info_types":
info_types,
"custom_info_types": [{
"info_type": {
"name": "PONumber"
},
"regex": {
"pattern": "[\d]"
},
"likelihood": "POSSIBLE",
}]
}
pdffile = filename
fileName = os.path.basename(pdffile)
doc = fitz.open(pdffile)
os.makedirs("output/" + fileName + "/pdftoImage", exist_ok=True)
os.makedirs("output/" + fileName + "/redactedImage", exist_ok=True)
numPages = doc.pageCount #number of page
print("Your document has " + str(numPages) + " pages.")
for pageNum in range(numPages):
page = doc.loadPage(pageNum)
pix = page.getPixmap()
output = "output/" + fileName + "/pdftoImage/page" + str(
pageNum).zfill(3) + ".png"
pix.writePNG(output)
pageNum = pageNum + 1
# If mime_type is not specified, guess it from the filename.
imgdir = "output/" + fileName + "/pdftoImage"
imglist = os.listdir(imgdir)
imgcount = len(imglist) # pic count
for i, f in enumerate(imglist):
filename = os.path.join(imgdir, f)
#print(filename)
if mime_type is None:
mime_guess = mimetypes.MimeTypes().guess_type(str(filename))
mime_type = mime_guess[0] or "application/octet-stream"
# Select the content type index from the list of supported types.
supported_content_types = {
None: 0, # "Unspecified"
"image/jpeg": 1,
"image/bmp": 2,
"image/png": 3,
"image/svg": 4,
"text/plain": 5,
}
content_type_index = supported_content_types.get(mime_type, 0)
# Construct the byte_item, containing the file's byte data.
with open(str(filename), mode="rb") as f:
byte_item = {"type": content_type_index, "data": f.read()}
#byte_item = encoded_string
# Convert the project id into a full resource id.
parent = dlp.project_path(project)
# Call the API.
response = dlp.redact_image(
parent,
inspect_config=inspect_config,
image_redaction_configs=image_redaction_configs,
byte_item=byte_item,
)
# Write out the results.
output_filename = "output/" + fileName + "/redactedImage/" + os.path.basename(
filename)
with open(output_filename, mode="wb") as fn:
fn.write(response.redacted_image)
print("Redacted Page : " + str(i + 1))
'''
print(
"Wrote {byte_count} to {filename}".format(
byte_count=len(response.redacted_image), filename=output_filename
)
)
'''
doc.close()
docBuild = fitz.open()
doc = docBuild
redactedimgdir = "output/" + fileName + "/redactedImage"
redactedimglist = os.listdir(redactedimgdir)
redactedimgcount = len(redactedimglist) # pic count
for i, f in enumerate(redactedimglist):
img = fitz.open(os.path.join(redactedimgdir,
f)) # open pic as document
#print(os.path.join(redactedimgdir, f))
#print(os.path.join(redactedimgdir, f))
rect = img[0].rect # pic dimension
pdfbytes = img.convertToPDF() # make a PDF stream
img.close() # no longer needed
imgPDF = fitz.open("pdf", pdfbytes) # open stream as PDF
page = doc.newPage(
width=rect.width, # new page with ...
height=rect.height) # pic dimension
page.showPDFpage(rect, imgPDF, 0) # image fills the page
doc.save("output/" + fileName + "/Redacted-" + fileName + ".pdf")
print("Document generated Successfully in " + "output/" + fileName +
"/Redacted-" + fileName)
def redact_imageTypes(project,
filename,
output_filename,
info_types,
min_likelihood=None,
mime_type=None):
# os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "kubernetes-e9dc8af4883c.json"
# Prepare info_types by converting the list of strings into a list of
# dictionaries (protos are also accepted).
info_types = [{"name": "ALL_BASIC"}]
# Prepare image_redaction_configs, a list of dictionaries. Each dictionary
# contains an info_type and optionally the color used for the replacement.
# The color is omitted in this sample, so the default (black) will be used.
image_redaction_configs = []
if info_types is not None:
for info_type in info_types:
image_redaction_configs.append({'info_type': info_type})
# Construct the configuration dictionary. Keys which are None may
# optionally be omitted entirely.
inspect_config = {
'min_likelihood': min_likelihood,
'info_types': info_types
}
# If mime_type is not specified, guess it from the filename.
if mime_type is None:
mime_guess = mimetypes.MimeTypes().guess_type(filename)
mime_type = mime_guess[0] or 'application/octet-stream'
# Select the content type index from the list of supported types.
supported_content_types = {
None: 0, # "Unspecified"
'image/jpeg': 1,
'image/bmp': 2,
'image/png': 3,
'image/svg': 4,
'text/plain': 5,
}
content_type_index = supported_content_types.get(mime_type, 0)
# Construct the byte_item, containing the file's byte data.
with open(filename, mode='rb') as f:
a = f.read()
byte_item = {'type': content_type_index, 'data': a}
print(byte_item)
# Convert the project id into a full resource id.
parent = dlp.project_path(project)
# Call the API.
response = dlp.redact_image(
parent,
inspect_config=inspect_config,
image_redaction_configs=image_redaction_configs,
byte_item=byte_item)
# Write out the results.
with open(output_filename, mode='wb') as f:
f.write(response.item.byte_item.data)
print('Written')