HoughCircles

import cv2
import numpy as np
from fpdf import FPDF
from pptx import Presentation
from pptx.util import Inches
import matplotlib.pyplot as plt

# Load the image
image_path = "C:/Users/HAL 9000/Downloads/image2.jpg"
image = cv2.imread(image_path)

# Convert to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Thresholding to create a binary image (air vs particles)
_, binary_image = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)

# Detect circular particles using HoughCircles
circles = cv2.HoughCircles(binary_image, cv2.HOUGH_GRADIENT, dp=1, minDist=20, param1=50, param2=30, minRadius=10, maxRadius=100)

# If circles are found, convert them to integers
if circles is not None:
    circles = np.round(circles[0, :]).astype("int")

# Function to detect non-circular particles (based on contour area and perimeter)
def detect_non_circular_particles(binary_image):
    contours, _ = cv2.findContours(binary_image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    non_circular_particles = []

    for contour in contours:
        # Approximate the contour to a polygon and compute its aspect ratio
        epsilon = 0.02 * cv2.arcLength(contour, True)
        approx = cv2.approxPolyDP(contour, epsilon, True)

        # Calculate the aspect ratio (width/height) of the bounding box
        x, y, w, h = cv2.boundingRect(approx)
        aspect_ratio = w / float(h) if h != 0 else 0
        # A non-circular particle will have an aspect ratio different from 1
        if aspect_ratio > 1.5 or aspect_ratio < 0.5:
            non_circular_particles.append(contour)

    return non_circular_particles

# Detect non-circular particles
non_circular_particles = detect_non_circular_particles(binary_image)

# Calculate the statistics for circular particles
circular_diameters = []
if circles is not None:
    for circle in circles:
        radius = circle[2]
        circular_diameters.append(2 * radius)

# Statistics for circular particles
circular_particles_count = len(circular_diameters)
average_diameter = np.mean(circular_diameters) if circular_particles_count > 0 else 0
std_dev_diameter = np.std(circular_diameters) if circular_particles_count > 0 else 0

# Area of circular and non-circular particles
circular_area = np.pi * (np.array(circular_diameters) / 2) ** 2
non_circular_area = sum([cv2.contourArea(cnt) for cnt in non_circular_particles])

# Area ratio
total_area = circular_area.sum() + non_circular_area
area_ratio_circular = circular_area.sum() / total_area
area_ratio_non_circular = non_circular_area / total_area

# Saving the segmented images for report purposes
# Save an image with circular particles marked
image_with_circles = image.copy()
if circles is not None:
    for circle in circles:
        cv2.circle(image_with_circles, (circle[0], circle[1]), circle[2], (0, 255, 0), 4)

cv2.imwrite("C:/Users/HAL 9000/Downloads/circular_particles.png", image_with_circles)

# Save an image with non-circular particles marked
image_with_non_circular = image.copy()
cv2.drawContours(image_with_non_circular, non_circular_particles, -1, (0, 0, 255), 2)
cv2.imwrite("C:/Users/HAL 9000/Downloads/non_circular_particles.png", image_with_non_circular)

# --- PDF Generation ---
pdf = FPDF()
pdf.add_page()

# Add title
pdf.set_font('Arial', 'B', 16)
pdf.cell(200, 10, txt="Particle Analysis Report", ln=True, align='C')

# Add statistics for circular particles
pdf.ln(10)
pdf.set_font('Arial', '', 12)
pdf.cell(200, 10, txt=f"Number of Circular Particles: {circular_particles_count}")
pdf.ln(10)
pdf.cell(200, 10, txt=f"Average Diameter of Circular Particles: {average_diameter:.2f} units")
pdf.ln(10)
pdf.cell(200, 10, txt=f"Standard Deviation of Diameters: {std_dev_diameter:.2f} units")
pdf.ln(10)

# Add Area Ratio
pdf.cell(200, 10, txt=f"Area Ratio (Circular Particles): {area_ratio_circular:.2f}")
pdf.ln(10)
pdf.cell(200, 10, txt=f"Area Ratio (Non-Circular Particles): {area_ratio_non_circular:.2f}")
pdf.ln(10)

# Add images to the PDF
pdf.image("C:/Users/HAL 9000/Downloads/circular_particles.png", x=10, y=60, w=90)
pdf.image("C:/Users/HAL 9000/Downloads/non_circular_particles.png", x=110, y=60, w=90)

# Save the PDF
output_pdf = "C:/Users/HAL 9000/Downloads/particle_analysis_report.pdf"
pdf.output(output_pdf)

print(f"PDF report generated and saved to {output_pdf}")

#Generate PPTX presentation with slides for each segment
presentation = Presentation()

# Circular particles slide
slide = presentation.slides.add_slide(presentation.slide_layouts[5])
slide.shapes.title.text = "Circular Particles"
slide.shapes.add_picture("C:/Users/HAL 9000/Downloads/circular_particles.png", Inches(1), Inches(1.5), Inches(6), Inches(4.5))
textbox = slide.shapes.add_textbox(Inches(1), Inches(6), Inches(6), Inches(1))
textbox.text = f"Number of Circular Particles: {circular_particles_count}\nAverage Diameter: {average_diameter:.2f} units"

# Non-Circular particles slide
slide = presentation.slides.add_slide(presentation.slide_layouts[5])
slide.shapes.title.text = "Non-Circular Particles"
slide.shapes.add_picture("C:/Users/HAL 9000/Downloads/non_circular_particles.png", Inches(1), Inches(1.5), Inches(6), Inches(4.5))
textbox = slide.shapes.add_textbox(Inches(1), Inches(6), Inches(6), Inches(1))
textbox.text = f"Area Ratio (Circular): {area_ratio_circular:.2f}\nArea Ratio (Non-Circular): {area_ratio_non_circular:.2f}"

#Save the PPTX
pptx_path = "C:/Users/HAL 9000/Downloads/particle_analysis_report.pptx"
presentation.save(pptx_path)

print(f"PPTX report generated and saved to {pptx_path}")

plt.show()