Extract images from document page area Leave feedback
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GroupDocs.Parser allows extracting images from specific rectangular areas of a document page, enabling precise image extraction from defined regions.
- GroupDocs.Parser for Python via .NET installed
- Sample documents with images
- Understanding of coordinate systems
To extract images from a specific rectangular area:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageAreaOptions, Rectangle, Point, Size
# Create an instance of Parser class
with Parser("./sample.pdf") as parser:
# Check if image extraction is supported
if not parser.features.images:
print("Image extraction not supported")
return
# Define the area (upper-left corner, 300x100 pixels)
area = Rectangle(Point(0, 0), Size(300, 100))
# Create options for the area
options = PageAreaOptions(area)
# Extract images from the specified area
images = parser.get_images(options)
if images:
print(f"Images found in area:")
for idx, image in enumerate(images):
print(f" Image {idx + 1}: {image.file_type}, Page {image.page.index + 1}")
else:
print("No images found in the specified area")
The following sample file is used in this example: sample.pdf
Expected behavior: Returns only images that are located within the specified rectangular area.
To extract images from several predefined areas:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageAreaOptions, Rectangle, Point, Size
import os
def extract_images_from_regions(file_path, regions, output_dir):
"""
Extract images from multiple predefined regions.
Args:
file_path: Path to document
regions: List of tuples (x, y, width, height)
output_dir: Directory to save images
"""
os.makedirs(output_dir, exist_ok=True)
with Parser(file_path) as parser:
if not parser.features.images:
print("Image extraction not supported")
return
for region_idx, (x, y, w, h) in enumerate(regions):
print(f"
Processing region {region_idx + 1}: ({x}, {y}, {w}x{h})")
# Create rectangle for this region
area = Rectangle(Point(x, y), Size(w, h))
options = PageAreaOptions(area)
# Extract images from this region
images = parser.get_images(options)
if images:
for img_idx, image in enumerate(images):
filename = f"region{region_idx + 1}_img{img_idx + 1}{image.file_type.extension}"
filepath = os.path.join(output_dir, filename)
image.save(filepath)
print(f" Saved: {filename}")
# Define regions (e.g., header, body, footer)
regions = [
(0, 0, 600, 100), # Header region
(0, 100, 600, 700), # Body region
(0, 800, 600, 100) # Footer region
]
# Extract images from regions
extract_images_from_regions("document.pdf", regions, "region_images")
The following sample file is used in this example: document.pdf
Expected behavior: Extracts and saves images organized by the region they were found in.
To extract images from a specific area on a specific page:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageAreaOptions, Rectangle, Point, Size
# Create an instance of Parser class
with Parser("document.pptx") as parser:
if not parser.features.images:
print("Image extraction not supported")
return
# Get document info
info = parser.get_document_info()
# Process specific page (e.g., first page)
page_index = 0
if page_index < info.page_count:
# Define area (center of page, 400x300)
area = Rectangle(Point(100, 100), Size(400, 300))
options = PageAreaOptions(area)
# Extract images from the area on the specific page
images = parser.get_images(page_index, options)
if images:
print(f"Images on page {page_index + 1} in specified area:")
for image in images:
print(f" Type: {image.file_type}")
print(f" Position: ({image.rectangle.left}, {image.rectangle.top})")
print(f" Size: {image.rectangle.width}x{image.rectangle.height}")
The following sample file is used in this example: document.pptx
Expected behavior: Extracts images from a specific area on a specific page.
To extract logo images from the header area:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageAreaOptions, Rectangle, Point, Size
import os
def extract_header_logos(file_path, output_dir):
"""
Extract logo images from document header area.
"""
os.makedirs(output_dir, exist_ok=True)
with Parser(file_path) as parser:
if not parser.features.images:
print("Image extraction not supported")
return
# Define header area (top 150 pixels, full width)
header_area = Rectangle(Point(0, 0), Size(1000, 150))
options = PageAreaOptions(header_area)
# Extract images from header
images = parser.get_images(options)
if images:
print(f"Found {len(list(images))} images in header
")
# Re-extract as iterator was consumed
images = parser.get_images(options)
for idx, image in enumerate(images):
filename = f"logo_{idx + 1}{image.file_type.extension}"
filepath = os.path.join(output_dir, filename)
image.save(filepath)
print(f"Saved logo: {filename}")
else:
print("No images found in header area")
# Usage
extract_header_logos("invoice.pdf", "extracted_logos")
The following sample file is used in this example: invoice.pdf
Expected behavior: Extracts logo or brand images typically found in document headers.
To extract images from document quadrants:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageAreaOptions, Rectangle, Point, Size
def extract_by_quadrant(file_path, page_width=600, page_height=800):
"""
Extract images by document quadrant (TL, TR, BL, BR).
"""
# Define quadrants
quadrant_size_w = page_width // 2
quadrant_size_h = page_height // 2
quadrants = {
'Top-Left': Rectangle(Point(0, 0), Size(quadrant_size_w, quadrant_size_h)),
'Top-Right': Rectangle(Point(quadrant_size_w, 0), Size(quadrant_size_w, quadrant_size_h)),
'Bottom-Left': Rectangle(Point(0, quadrant_size_h), Size(quadrant_size_w, quadrant_size_h)),
'Bottom-Right': Rectangle(Point(quadrant_size_w, quadrant_size_h), Size(quadrant_size_w, quadrant_size_h))
}
with Parser(file_path) as parser:
if not parser.features.images:
print("Image extraction not supported")
return
for quadrant_name, area in quadrants.items():
options = PageAreaOptions(area)
images = parser.get_images(options)
if images:
image_list = list(images)
print(f"{quadrant_name}: {len(image_list)} images")
else:
print(f"{quadrant_name}: 0 images")
# Usage
extract_by_quadrant("layout.pdf")
The following sample file is used in this example: layout.pdf
Expected behavior: Categorizes and counts images by their location in document quadrants.
To filter images by size within an area:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageAreaOptions, Rectangle, Point, Size
import os
def extract_large_images_from_area(file_path, area_rect, min_width, min_height, output_dir):
"""
Extract images larger than specified size from an area.
"""
os.makedirs(output_dir, exist_ok=True)
with Parser(file_path) as parser:
if not parser.features.images:
print("Image extraction not supported")
return
options = PageAreaOptions(area_rect)
images = parser.get_images(options)
if not images:
print("No images found in area")
return
saved_count = 0
for image in images:
# Check image size
if image.rectangle.width >= min_width and image.rectangle.height >= min_height:
filename = f"large_image_{saved_count + 1}{image.file_type.extension}"
filepath = os.path.join(output_dir, filename)
image.save(filepath)
print(f"Saved: {filename} ({image.rectangle.width}x{image.rectangle.height})")
saved_count += 1
print(f"
Total large images saved: {saved_count}")
# Usage - extract images larger than 100x100 from center area
center_area = Rectangle(Point(100, 100), Size(400, 600))
extract_large_images_from_area("document.pdf", center_area, 100, 100, "large_images")
The following sample file is used in this example: document.pdf
Expected behavior: Extracts only images that meet the minimum size criteria within the specified area.
- Always check
parser.features.imagesbefore extracting images - Coordinates are in document-specific units (points or pixels)
- The origin (0, 0) is at the top-left corner
- Images partially overlapping the area boundary are included
- Use
get_images(page_index, options)to extract from a specific page area - Empty collections are returned if no images are found in the area (not
None)
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