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import gradio as gr
import numpy as np
import fitz # PyMuPDF
import spaces
from ultralytics import YOLO
# Load the trained model
model = YOLO("best.engine")
# Define the class indices for figures and tables
figure_class_index = 3 # class index for figures
table_class_index = 4 # class index for tables
# Function to perform inference on an image and return bounding boxes for figures and tables
def infer_image_and_get_boxes(image, confidence_threshold=0.6):
results = model(image)
boxes = [
(int(box.xyxy[0][0]), int(box.xyxy[0][1]), int(box.xyxy[0][2]), int(box.xyxy[0][3]))
for result in results for box in result.boxes
if int(box.cls[0]) in {figure_class_index, table_class_index} and box.conf[0] > confidence_threshold
]
return boxes
# Function to crop images from the boxes
def crop_images_from_boxes(image, boxes, scale_factor):
cropped_images = [
image[int(y1 * scale_factor):int(y2 * scale_factor), int(x1 * scale_factor):int(x2 * scale_factor)]
for (x1, y1, x2, y2) in boxes
]
return cropped_images
@spaces.GPU
def process_pdf(pdf_file):
# Open the PDF file
doc = fitz.open(pdf_file)
all_cropped_images = []
# Set the DPI for inference and high resolution for cropping
low_dpi = 50
high_dpi = 300
# Calculate the scaling factor
scale_factor = high_dpi / low_dpi
# Pre-cache all page pixmaps at low DPI
low_res_pixmaps = [page.get_pixmap(dpi=low_dpi) for page in doc]
# Loop through each page
for page_num, low_res_pix in enumerate(low_res_pixmaps):
low_res_img = np.frombuffer(low_res_pix.samples, dtype=np.uint8).reshape(low_res_pix.height, low_res_pix.width, 3)
# Get bounding boxes from low DPI image
boxes = infer_image_and_get_boxes(low_res_img)
if boxes:
# Load high DPI image for cropping only if boxes are found
high_res_pix = doc[page_num].get_pixmap(dpi=high_dpi)
high_res_img = np.frombuffer(high_res_pix.samples, dtype=np.uint8).reshape(high_res_pix.height, high_res_pix.width, 3)
# Crop images at high DPI
cropped_imgs = crop_images_from_boxes(high_res_img, boxes, scale_factor)
all_cropped_images.extend(cropped_imgs)
return all_cropped_images
# Create Gradio interface
iface = gr.Interface(
fn=process_pdf,
inputs=gr.File(label="Upload a PDF"),
outputs=gr.Gallery(label="Cropped Figures and Tables from PDF Pages"),
title="Fast document layout analysis based on YOLOv10",
description="Upload a PDF file to get cropped figures and tables from each page."
)
# Launch the app
iface.launch()
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