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import subprocess
import streamlit as st
import cv2
import numpy as np
from PIL import Image
import pytesseract
def get_pdf_page_count(pdf_path):
try:
# Running pdfinfo command to get information about the PDF
result = subprocess.run(['pdfinfo', pdf_path], stdout=subprocess.PIPE, text=True)
# Parsing the output to find the line with the number of pages
for line in result.stdout.split('\n'):
if 'Pages:' in line:
return int(line.split(':')[1].strip())
except Exception as e:
print(f"An error occurred: {e}")
return None
#configurable extract rectange rectangle size
def extract_rectangle_from_image(gray, min_width, min_height):
bounding_boxes = []
#gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 50, 150, apertureSize=3)
#edges = cv2.Canny(gray, 10, 200, apertureSize=3)
kernel = np.ones((3,3), np.uint8)
dilated_edges = cv2.dilate(edges, kernel, iterations=1)
contours, _ = cv2.findContours(dilated_edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
#contours, _ = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
index = 0
for cnt in contours:
approx = cv2.approxPolyDP(cnt, 0.01*cv2.arcLength(cnt, True), True)
#approx = cv2.approxPolyDP(cnt, 0.1*cv2.arcLength(cnt, True), True)
if len(approx) == 4: # Rectangle check
x, y, w, h = cv2.boundingRect(approx)
# print(f"x: {x}, y: {y}, w: {w}, h: {h}")
if w >= min_width and h >= min_height:
bounding_boxes.append((x, y, w, h))
#print(x, y, w, h)
return bounding_boxes
def is_close(box1, box2, threshold=10):
# Calculate the distance between the top-left corners of the two boxes
distance = ((box1[0] - box2[0]) ** 2 + (box1[1] - box2[1]) ** 2) ** 0.5
return distance < threshold
def remove_close_boxes(boxes, threshold=10):
kept_boxes = []
for box in boxes:
# Assume the box is not close to others by default
is_close_to_others = False
for kept_box in kept_boxes:
if is_close(box, kept_box, threshold):
is_close_to_others = True
break
# If the box is not close to any box we've kept, add it to the list of kept boxes
if not is_close_to_others:
kept_boxes.append(box)
return kept_boxes
def is_contained(box1, box2):
"""
Check if box1 is contained within box2.
Each box is defined as (x, y, w, h).
"""
x1, y1, w1, h1 = box1
x2, y2, w2, h2 = box2
# Check if all corners of box1 are inside box2
return x2 <= x1 and y2 <= y1 and x2 + w2 >= x1 + w1 and y2 + h2 >= y1 + h1
def remove_contained_boxes(boxes):
"""
Remove boxes that are contained within other boxes.
"""
non_contained_boxes = []
for i, box1 in enumerate(boxes):
# Check if there's another box that contains box1
if not any(is_contained(box1, box2) for j, box2 in enumerate(boxes) if i != j):
non_contained_boxes.append(box1)
return non_contained_boxes
def draw_colored_boxes_on_image_np(image, boxes_list,color_tuple):
for x, y, w, h in boxes_list:
#x, y, w, h = box[0]
cv2.rectangle(image, (x, y), (x + w, y + h), color_tuple, thickness=5)
def is_filled_rectangle(image, rect, background_threshold=10, variance_threshold=0.1):
x, y, w, h = rect
# roi = image[y+1:y+h-1, x+1:x+w-1]
roi = image[y + 10:y + h - 10, x + 10:x + w - 10]
return np.all(roi == 0)
def get_below_box(image_np, x, y,width,step=15):
#print("x,y,width="+str(x)+","+str(y)+","+str(width))
index_y = -1
#print("get_below_box"+str(image_np.shape))
if y+step < image_np.shape[0]:
index_y = y
while index_y+step < image_np.shape[0]:
#print(str( np.all(image_np[index_y:index_y+step,x:x+width] == 255)))
# image_np_copy = image_np.copy()
# bgr_image = cv2.cvtColor(image_np_copy, cv2.COLOR_GRAY2BGR)
# cv2.rectangle(bgr_image, (x, index_y), (x + width, index_y +step), color_tuple, thickness=5)
# display_image_np(bgr_image)
if np.all(image_np[index_y:index_y+step,x:x+width] == 255):
# index_y += step
break
index_y += step
return index_y
def get_above_box(image_np, x, y,width,step=15):
#print("x,y,width="+str(x)+","+str(y)+","+str(width))
index_y = -1
#print("get_below_box"+str(image_np.shape))
if y-step > 0:
index_y = y
while index_y-step > 0:
#print(str( np.all(image_np[index_y:index_y+step,x:x+width] == 255)))
# image_np_copy = image_np.copy()
# bgr_image = cv2.cvtColor(image_np_copy, cv2.COLOR_GRAY2BGR)
# color_tuple=(0, 255, 0)
# cv2.rectangle(bgr_image, (x, index_y-step), (x + width, index_y), color_tuple, thickness=5)
# display_image_np(bgr_image)
if np.all(image_np[index_y-step:index_y,x:x+width] == 255):
# index_y += step
break
index_y -= step
return index_y
def is_note_rectangle(image_np, rect):
x, y, w, h = rect
roi = image_np[y+1:y+h-1, x+1:x+w-1]
roi_converted = Image.fromarray(cv2.cvtColor(roi, cv2.COLOR_BGR2RGB))
text = pytesseract.image_to_string(roi_converted)
text = text.strip()
note_str="note"
# print("is note text box="+str(text.lower().startswith(note_str.lower())))
return text.lower().startswith(note_str.lower())
def extract_bounding_boxes_from_image_np(image_np, bounding_boxes_list, above_check_offset, above_caption_offset, color_tuple):
image_np_copy=image_np.copy()
rect_content_list=[]
above_rect_content_list=[]
figures_image_list=[]
tables_image_list=[]
index = 0
for box in bounding_boxes_list:
x, y, w, h = box
if not is_filled_rectangle(image_np_copy, box):
# print("box="+str(box)+"not filled")
y_index= get_below_box(image_np, x, y+h,w)
if y_index == -1 or is_note_rectangle(image_np_copy, box):
# print("below text not found")
rect_content =image_np[y:y+h, x:x+w]
# rect_content_list.append(rect_content)
cv2.rectangle(image_np_copy, (x, y), (x+w, y+h), color_tuple, cv2.FILLED)
else:
# print("below text found")
rect_content =image_np[y:y_index, x:x+w]
# rect_content_list.append(rect_content)
cv2.rectangle(image_np_copy, (x, y), (x+w, y_index), color_tuple, cv2.FILLED)
cv2.rectangle(image_np_copy, (x, y), (x+w, y+h), color_tuple, cv2.FILLED)
above_box_y= get_above_box(image_np, x, y,w)
if above_box_y == -1 or above_box_y == y:
# print("box="+str(box)+"no above box")
above_rect_content_list.append(None)
rect_content_list.append(rect_content)
else:
# print("box="+str(box)+"above box exist")
above_rect_content = image_np[above_box_y:y, x:x+w]
# above_rect_content_list.append(above_rect_content)
above_converted = Image.fromarray(cv2.cvtColor(above_rect_content, cv2.COLOR_BGR2RGB))
text = pytesseract.image_to_string(above_converted)
text = text.strip()
figure_str ="Figure"
table_str ="Table"
if text.lower().startswith(figure_str.lower()):
# print(text)
figures_image_list.append((text,rect_content))
elif text.lower().startswith(table_str.lower()):
# print(text)
tables_image_list.append((text,rect_content))
else:
print("*** text box have above content")
above_rect_content_list.append((text, rect_content))
rect_content_list.append(rect_content)
cv2.rectangle(image_np_copy, (x, above_box_y), (x+w, y), color_tuple, cv2.FILLED)
# above_rect_content = image_np[y-above_check_offset:y, x:x+w]
# if np.all(above_rect_content == 255):
# # print("box="+str(box)+"above all white")
# above_rect_content_list.append(None)
# else:
# # print("box="+str(box)+"above not all white")
# above_rect_content = image_np[y-above_caption_offset:y, x:x+w]
# above_rect_content_list.append(above_rect_content)
# cv2.rectangle(image_np_copy, (x, y), (x+w, y-above_caption_offset), color_tuple, cv2.FILLED)
index += 1
# else:
# print("box="+str(box)+"filled")
return rect_content_list,above_rect_content_list, figures_image_list, tables_image_list, image_np_copy
def find_hor_lines_in_image_np(min_width, min_height,image_np):
# Apply a horizontal kernel to emphasize horizontal lines
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1050, 5)) # Adjust size according to your document
morphed = cv2.morphologyEx(image_np, cv2.MORPH_CLOSE, kernel)
# Detect edges
edges = cv2.Canny(morphed, 50, 150, apertureSize=3)
# Detect lines using HoughLinesP
lines = cv2.HoughLinesP(edges, 1, np.pi / 180, threshold=100, minLineLength=100, maxLineGap=10) # Adjust parameters as needed
return lines
def draw_colored_lines_on_image_np(image, lines,color_tuple):
for line in lines:
x1, y1, x2, y2 = line[0]
cv2.line(image, (x1, y1), (x2, y2), color_tuple, 3)
def segment_image_np(image_np,hor_lines_list):
# print("in segment_image_np image_np start")
# display_image_np(image_np)
# print("in segment_image_np image_np end")
segments = []
previous_y = 0
for line in sorted(hor_lines_list, key=lambda x: x[0][1]): # Sort lines by their y-coordinate
x1, y1, x2, y2 = line[0]
segment = image_np[previous_y:y1, :]
segments.append(segment)
previous_y = y2 # Update to start the next segment from the end of the current line
# Don't forget the last segment
last_segment =image_np[previous_y:, :]
segments.append(last_segment)
return segments
def filter_segments_by_min_height(segments, min_height):
return [segment for segment in segments if segment.shape[0] > min_height]
def draw_edges(np_image):
color = (0, 255, 0) # Green
# Define the thickness of the rectangle lines
thickness = 5
# Get the dimensions of the image
try:
height, width = np_image.shape[:2]
except Exception as e:
print("An error occurred:", e)
# Coordinates for the rectangle: start from (0,0) to (width, height)
# We draw from 0+thickness//2 and width-thickness//2 to respect the thickness and not go out of bounds
cv2.rectangle(np_image, (thickness // 2, thickness // 2), (width - thickness // 2, height - thickness // 2), color,
thickness)
def is_image_np_two_columns(image_np,horizontal_margin,vertical_margin):
page_x_center = image_np.shape[1]//2
page_height=image_np.shape[0]
image_middle_np =image_np[vertical_margin:(page_height-vertical_margin), page_x_center-horizontal_margin:page_x_center+horizontal_margin]
#display_image_np(image_middle_np)
return np.all(image_middle_np == 255)
def extract_two_columns_text(image_index,image_np,debug):
# formatted_index_string = f"{index:03d}"
if is_image_np_two_columns(image_np,20,10):
page_x_center = image_np.shape[1] // 2
# print(page_x_center)
temp_array = image_np.copy()
left_column_array = temp_array[:, :page_x_center]
temp_array = image_np.copy()
right_column_array = temp_array[:, page_x_center:]
left_column_img = Image.fromarray(cv2.cvtColor(left_column_array, cv2.COLOR_BGR2RGB))
left_column_array_bgr_image = cv2.cvtColor(left_column_array, cv2.COLOR_GRAY2BGR)
draw_edges(left_column_array_bgr_image)
# imageio.imwrite("/content/gdrive/MyDrive/Avatar/demo_pdf_ingestion_steps/page_"+formatted_index_string + "step8_left_column.png", left_column_img)
right_column_img = Image.fromarray(cv2.cvtColor(right_column_array, cv2.COLOR_BGR2RGB))
right_column_array_bgr_image = cv2.cvtColor(right_column_array, cv2.COLOR_GRAY2BGR)
draw_edges(right_column_array_bgr_image)
# imageio.imwrite("/content/gdrive/MyDrive/Avatar/demo_pdf_ingestion_steps/page_"+formatted_index_string + "step8_right_column.png", right_column_img)
# if debug:
# print("left column image start")
# # display(left_column_img)
# # st.image(Image.fromarray(left_column_array_bgr_image)) # to_be_displayed
# print("left column image end")
# print("right column image start")
# # display(right_column_img)
# # st.image(Image.fromarray(right_column_array_bgr_image)) # to_be_displayed
# print("right column image end")
left_text = pytesseract.image_to_string(left_column_img)
# with open("/content/gdrive/MyDrive/Avatar/demo_pdf_ingestion_steps/page_"+formatted_index_string + "step9_left_column_text.txt", 'w') as file:
# file.write(left_text)
# print("Extracted Text:\n", left_text)
right_text = pytesseract.image_to_string(right_column_img)
# with open("/content/gdrive/MyDrive/Avatar/demo_pdf_ingestion_steps/page_"+formatted_index_string + "step9_right_column_text.txt", 'w') as file:
# file.write(right_text)
# print("Extracted Text:\n", right_text)
return left_text + right_text
else:
return "error"
def get_where_image_np_two_columns_stops(image_np,horizontal_margin,vertical_margin):
page_x_center = image_np.shape[1]//2
page_height=image_np.shape[0]
image_middle_np =image_np[vertical_margin:(page_height-vertical_margin), page_x_center-horizontal_margin:page_x_center+horizontal_margin]
#display_image_np(image_middle_np)
return np.where(image_middle_np != 255)
# indices = np.where(image_middle_np != 255)
# print(len(indices[0]))
# for i in range(len(indices[0])):
# print(f"Index: {indices[0][i], indices[1][i]}, Value: {image_middle_np[indices[0][i], indices[1][i]]}")
def gray_pdf_image_np_to_text(image_index,gray_pdf_image_np, debug=False):
bounding_boxes_list = extract_rectangle_from_image(gray_pdf_image_np, 500, 20)
bounding_boxes_list = remove_close_boxes (bounding_boxes_list, 10)
bounding_boxes_list = remove_contained_boxes(bounding_boxes_list)
if debug:
bgr_image = cv2.cvtColor(gray_pdf_image_np, cv2.COLOR_GRAY2BGR)
color_tuple = (0, 255, 0)
# print("bounding_boxes_list")
# print(bounding_boxes_list)
draw_colored_boxes_on_image_np(bgr_image, bounding_boxes_list, color_tuple)
# st.image(Image.fromarray(bgr_image)) #to_be_displayed
text_box_list, above_test_box_list,figures_image_list,tables_image_list, cropped_image = extract_bounding_boxes_from_image_np(gray_pdf_image_np,
bounding_boxes_list, 30,
50, (255, 255, 255))
if debug:
debug_text_box_index = 0
for text_box, above_text_box in zip(text_box_list, above_test_box_list):
# print("text box start")
# if above_text_box is not None:
# print(above_text_box[0])#to_be_displayed
# st.write(above_text_box[0])#to_be_displayed
# st.image(Image.fromarray(above_text_box[1]))#to_be_displayed
# st.write(text)
# st.image(Image.fromarray(text_box))#to_be_displayed
debug_text_box_index = debug_text_box_index + 1
# for figure in figures_image_list:
# print(figure[0])
# st.write(figure[0])#to_be_displayed
# st.image(Image.fromarray(figure[1]))#to_be_displayed
# for table in tables_image_list:
# print(table[0])
# st.write(table[0])#to_be_displayed
# st.image(Image.fromarray(table[1]))#to_be_displayed
# st.image(Image.fromarray(cropped_image))#to_be_displayed
found_hor_lines_list = find_hor_lines_in_image_np(1050, 5, cropped_image)
if found_hor_lines_list is not None:
bgr_image = cv2.cvtColor(gray_pdf_image_np, cv2.COLOR_GRAY2BGR)
draw_colored_lines_on_image_np(bgr_image, found_hor_lines_list, (0, 255, 0))
# print("detected Lines start")
# # st.image(Image.fromarray(bgr_image)) #to_be_displayed
#
# print("detected lines end")
page_segment_np_list = segment_image_np(cropped_image, found_hor_lines_list)
if debug:
debug_page_segment_index = 0
for element in page_segment_np_list:
# print("element start")
bgr_image = cv2.cvtColor(element, cv2.COLOR_GRAY2BGR)
draw_edges(bgr_image)
# st.image(Image.fromarray(bgr_image))#to_be_displayed
debug_page_segment_index = debug_page_segment_index + 1
# print("element end")
min_height_filtered_page_segment_np_list = filter_segments_by_min_height(page_segment_np_list, 50)
max_height_image = max(min_height_filtered_page_segment_np_list, key=lambda image: image.shape[0])
else:
max_height_image = cropped_image.copy()
# st.write("selected segment")
# print("max height image start")
# st.image(Image.fromarray(max_height_image))#to_be_displayed
# print("max height image end")
# print("start text extraction")
text=extract_two_columns_text(image_index,max_height_image,debug)
# print("gray_pdf_image_np_to_text extracted text",text)
if text == "error":
print("not two columns")
max_height_image_converted = Image.fromarray(cv2.cvtColor(max_height_image, cv2.COLOR_BGR2RGB))
text = pytesseract.image_to_string(max_height_image_converted)
text = text.strip()
toc_str="table of contents"
# print("Extracted Text:\n", text)
if text.lower().startswith(toc_str.lower()):
#if "Table of Contents" in text:
print("Table of Contents")
# display_image_np(max_height_image)
#print(text)
return None, None, None, "Table of Contents"
else:
print("not Table of Contents")
indeces_stop=get_where_image_np_two_columns_stops(max_height_image,20,10)
print(indeces_stop[0][0])
print(max_height_image.shape[0])
y_start=get_above_box(max_height_image, 0, indeces_stop[0][0],max_height_image.shape[1])
if debug:
bgr_image = cv2.cvtColor(max_height_image, cv2.COLOR_GRAY2BGR)
color_tuple=(0, 255, 0)
cv2.rectangle(bgr_image, (0, y_start), (max_height_image.shape[1], max_height_image.shape[0]), color_tuple, thickness=5)
print("still in the middle start")
# st.image(Image.fromarray(bgr_image))
print("still in the middle end")
left_over_content =max_height_image[y_start:max_height_image.shape[0], 0:max_height_image.shape[1]]
if debug:
print("left over start")
# st.image(Image.fromarray(left_over_content))
print("left over end")
max_height_image_copy=max_height_image.copy()
cv2.rectangle(max_height_image_copy, (0, y_start), (max_height_image.shape[1], max_height_image.shape[0]), (255, 255, 255), cv2.FILLED)
if debug:
print("no left over start")
# st.image(Image.fromarray(max_height_image_copy))
print("no left over end")
text=extract_two_columns_text(image_index,max_height_image_copy,debug)
if text == "error":
return None, None, None, "error"
# return()
else:
return figures_image_list,tables_image_list,text_box_list,text
else:
return figures_image_list,tables_image_list,text_box_list,text
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