document_redaction / tools /file_conversion.py
seanpedrickcase's picture
Comprehend now uses custom spacy recognisers on top of defaults. Added zoom functionality to annotator. Fixed some pdf mediabox issues and redacted image output issues.
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from pdf2image import convert_from_path, pdfinfo_from_path
from tools.helper_functions import get_file_path_end, output_folder, detect_file_type
from PIL import Image, ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
import os
import gradio as gr
import time
import json
import pymupdf
from gradio import Progress
from typing import List, Optional
image_dpi = 300.0
def is_pdf_or_image(filename):
"""
Check if a file name is a PDF or an image file.
Args:
filename (str): The name of the file.
Returns:
bool: True if the file name ends with ".pdf", ".jpg", or ".png", False otherwise.
"""
if filename.lower().endswith(".pdf") or filename.lower().endswith(".jpg") or filename.lower().endswith(".jpeg") or filename.lower().endswith(".png"):
output = True
else:
output = False
return output
def is_pdf(filename):
"""
Check if a file name is a PDF.
Args:
filename (str): The name of the file.
Returns:
bool: True if the file name ends with ".pdf", False otherwise.
"""
return filename.lower().endswith(".pdf")
# %%
## Convert pdf to image if necessary
def convert_pdf_to_images(pdf_path:str, page_min:int = 0, image_dpi:float = image_dpi, progress=Progress(track_tqdm=True)):
# Get the number of pages in the PDF
page_count = pdfinfo_from_path(pdf_path)['Pages']
print("Number of pages in PDF: ", str(page_count))
images = []
# Open the PDF file
#for page_num in progress.tqdm(range(0,page_count), total=page_count, unit="pages", desc="Converting pages"): range(page_min,page_count): #
for page_num in progress.tqdm(range(page_min,page_count), total=page_count, unit="pages", desc="Preparing pages"):
print("Converting page: ", str(page_num + 1))
# Convert one page to image
out_path = pdf_path + "_" + str(page_num) + ".png"
# Ensure the directory exists
os.makedirs(os.path.dirname(out_path), exist_ok=True)
# Check if the image already exists
if os.path.exists(out_path):
#print(f"Loading existing image from {out_path}.")
image = Image.open(out_path) # Load the existing image
else:
image_l = convert_from_path(pdf_path, first_page=page_num+1, last_page=page_num+1, dpi=image_dpi, use_cropbox=True, use_pdftocairo=False)
image = image_l[0]
# Convert to greyscale
image = image.convert("L")
image.save(out_path, format="PNG") # Save the new image
# If no images are returned, break the loop
if not image:
print("Conversion of page", str(page_num), "to file failed.")
break
# print("Conversion of page", str(page_num), "to file succeeded.")
# print("image:", image)
images.append(out_path)
print("PDF has been converted to images.")
# print("Images:", images)
return images
# %% Function to take in a file path, decide if it is an image or pdf, then process appropriately.
def process_file(file_path):
# Get the file extension
file_extension = os.path.splitext(file_path)[1].lower()
# Check if the file is an image type
if file_extension in ['.jpg', '.jpeg', '.png']:
print(f"{file_path} is an image file.")
# Perform image processing here
img_object = [Image.open(file_path)]
# Load images from the file paths
# Check if the file is a PDF
elif file_extension == '.pdf':
print(f"{file_path} is a PDF file. Converting to image set")
# Run your function for processing PDF files here
img_object = convert_pdf_to_images(file_path)
else:
print(f"{file_path} is not an image or PDF file.")
img_object = ['']
return img_object
def get_input_file_names(file_input):
'''
Get list of input files to report to logs.
'''
all_relevant_files = []
#print("file_input:", file_input)
if isinstance(file_input, str):
file_input_list = [file_input]
for file in file_input_list:
if isinstance(file, str):
file_path = file
else:
file_path = file.name
file_path_without_ext = get_file_path_end(file_path)
#print("file:", file_path)
file_extension = os.path.splitext(file_path)[1].lower()
file_name_with_extension = file_path_without_ext + file_extension
# Check if the file is an image type
if file_extension in ['.jpg', '.jpeg', '.png', '.pdf', '.xlsx', '.csv', '.parquet']:
all_relevant_files.append(file_path_without_ext)
all_relevant_files_str = ", ".join(all_relevant_files)
#print("all_relevant_files_str:", all_relevant_files_str)
return all_relevant_files_str, file_name_with_extension
def prepare_image_or_pdf(
file_paths: List[str],
in_redact_method: str,
in_allow_list: Optional[List[List[str]]] = None,
latest_file_completed: int = 0,
out_message: List[str] = [],
first_loop_state: bool = False,
number_of_pages:int = 1,
current_loop_page_number:int=0,
progress: Progress = Progress(track_tqdm=True)
) -> tuple[List[str], List[str]]:
"""
Prepare and process image or text PDF files for redaction.
This function takes a list of file paths, processes each file based on the specified redaction method,
and returns the output messages and processed file paths.
Args:
file_paths (List[str]): List of file paths to process.
in_redact_method (str): The redaction method to use.
in_allow_list (Optional[List[List[str]]]): List of allowed terms for redaction.
latest_file_completed (int): Index of the last completed file.
out_message (List[str]): List to store output messages.
first_loop_state (bool): Flag indicating if this is the first iteration.
number_of_pages (int): integer indicating the number of pages in the document
progress (Progress): Progress tracker for the operation.
Returns:
tuple[List[str], List[str]]: A tuple containing the output messages and processed file paths.
"""
tic = time.perf_counter()
# If this is the first time around, set variables to 0/blank
if first_loop_state==True:
print("first_loop_state is True")
latest_file_completed = 0
out_message = []
else:
print("Now attempting file:", str(latest_file_completed))
# This is only run when a new page is loaded, so can reset page loop values. If end of last file (99), current loop number set to 999
# if latest_file_completed == 99:
# current_loop_page_number = 999
# page_break_return = False
# else:
# current_loop_page_number = 0
# page_break_return = False
# If out message or converted_file_paths are blank, change to a list so it can be appended to
if isinstance(out_message, str):
out_message = [out_message]
converted_file_paths = []
image_file_paths = []
pymupdf_doc = []
if not file_paths:
file_paths = []
if isinstance(file_paths, str):
file_path_number = 1
else:
file_path_number = len(file_paths)
print("Current_loop_page_number at start of prepare_image_or_pdf function is:", current_loop_page_number)
print("Number of file paths:", file_path_number)
print("Latest_file_completed:", latest_file_completed)
latest_file_completed = int(latest_file_completed)
# If we have already redacted the last file, return the input out_message and file list to the relevant components
if latest_file_completed >= file_path_number:
print("Last file reached, returning files:", str(latest_file_completed))
if isinstance(out_message, list):
final_out_message = '\n'.join(out_message)
else:
final_out_message = out_message
return final_out_message, converted_file_paths, image_file_paths, number_of_pages, number_of_pages, pymupdf_doc
#in_allow_list_flat = [item for sublist in in_allow_list for item in sublist]
progress(0.1, desc='Preparing file')
if isinstance(file_paths, str):
file_paths_list = [file_paths]
file_paths_loop = file_paths_list
else:
file_paths_list = file_paths
file_paths_loop = [file_paths_list[int(latest_file_completed)]]
#print("file_paths_loop:", str(file_paths_loop))
#for file in progress.tqdm(file_paths, desc="Preparing files"):
for file in file_paths_loop:
if isinstance(file, str):
file_path = file
else:
file_path = file.name
file_path_without_ext = get_file_path_end(file_path)
#print("file:", file_path)
file_extension = os.path.splitext(file_path)[1].lower()
# Check if the file is an image type
if file_extension in ['.jpg', '.jpeg', '.png']:
in_redact_method = "Quick image analysis - typed text"
# If the file loaded in is json, assume this is a textract response object. Save this to the output folder so it can be found later during redaction and go to the next file.
if file_extension in ['.json']:
json_contents = json.load(file_path)
# Write the response to a JSON file
out_folder = output_folder + file_path
with open(file_path, 'w') as json_file:
json.dump(json_contents, out_folder, indent=4) # indent=4 makes the JSON file pretty-printed
continue
#if file_path:
# file_path_without_ext = get_file_path_end(file_path)
if not file_path:
out_message = "No file selected"
print(out_message)
return out_message, converted_file_paths, image_file_paths, number_of_pages, number_of_pages, pymupdf_doc
if in_redact_method == "Quick image analysis - typed text" or in_redact_method == "Complex image analysis - docs with handwriting/signatures (AWS Textract)":
# Analyse and redact image-based pdf or image
if is_pdf_or_image(file_path) == False:
out_message = "Please upload a PDF file or image file (JPG, PNG) for image analysis."
print(out_message)
return out_message, converted_file_paths, image_file_paths, number_of_pages, number_of_pages, pymupdf_doc
converted_file_path = process_file(file_path)
image_file_path = converted_file_path
#print("Out file path at image conversion step:", converted_file_path)
elif in_redact_method == "Simple text analysis - PDFs with selectable text":
if is_pdf(file_path) == False:
out_message = "Please upload a PDF file for text analysis."
print(out_message)
return out_message, converted_file_paths, image_file_paths, number_of_pages, number_of_pages, pymupdf_doc
converted_file_path = file_path # Pikepdf works with the basic unconverted pdf file
image_file_path = process_file(file_path)
converted_file_paths.append(converted_file_path)
image_file_paths.extend(image_file_path)
# If a pdf, load as a pymupdf document
if is_pdf(file_path):
pymupdf_doc = pymupdf.open(file_path)
#print("pymupdf_doc:", pymupdf_doc)
elif is_pdf_or_image(file_path): # Alternatively, if it's an image
# Convert image to a pymupdf document
pymupdf_doc = pymupdf.open() # Create a new empty document
img = Image.open(file_path) # Open the image file
rect = pymupdf.Rect(0, 0, img.width, img.height) # Create a rectangle for the image
page = pymupdf_doc.new_page(width=img.width, height=img.height) # Add a new page
page.insert_image(rect, filename=file_path) # Insert the image into the page
# Ensure to save the document after processing
#pymupdf_doc.save(output_path) # Uncomment and specify output_path if needed
#pymupdf_doc.close() # Close the PDF document
toc = time.perf_counter()
out_time = f"File '{file_path_without_ext}' prepared in {toc - tic:0.1f} seconds."
print(out_time)
out_message.append(out_time)
out_message_out = '\n'.join(out_message)
number_of_pages = len(image_file_paths)
print("At end of prepare_image_or_pdf function - current_loop_page_number:", current_loop_page_number)
return out_message_out, converted_file_paths, image_file_paths, number_of_pages, number_of_pages, pymupdf_doc
def convert_text_pdf_to_img_pdf(in_file_path:str, out_text_file_path:List[str], image_dpi:float=image_dpi):
file_path_without_ext = get_file_path_end(in_file_path)
out_file_paths = out_text_file_path
# Convert annotated text pdf back to image to give genuine redactions
print("Creating image version of redacted PDF to embed redactions.")
pdf_text_image_paths = process_file(out_text_file_path[0])
out_text_image_file_path = output_folder + file_path_without_ext + "_text_redacted_as_img.pdf"
pdf_text_image_paths[0].save(out_text_image_file_path, "PDF" ,resolution=image_dpi, save_all=True, append_images=pdf_text_image_paths[1:])
# out_file_paths.append(out_text_image_file_path)
out_file_paths = [out_text_image_file_path]
out_message = "PDF " + file_path_without_ext + " converted to image-based file."
print(out_message)
#print("Out file paths:", out_file_paths)
return out_message, out_file_paths