conv_Excel.py

import pandas as pd
import os
import cv2
from featureExtraction import ShapeSizeFeature
from skimage.color import rgb2gray
import numpy as np
from pathlib import Path



def extract_features(image_path):
    I = cv2.imread(image_path)
    Ig = rgb2gray(I)
    normIg = np.zeros(Ig.shape)
    Ig1=cv2.normalize(Ig,normIg, 0, 255, cv2.NORM_MINMAX)
    blur = cv2.GaussianBlur(np.uint8(Ig1), (15, 15), 0)
    ret, thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
    thresh=np.invert(thresh)
    number_of_white_pix = np.sum(thresh == 255)
    
    
    # 
    S = ShapeSizeFeature(thresh)
    feature1 = S['Compactness'][0]
    feature2 = S['Roundness'][0]
    feature3 = S['SF3'][0]
    feature4 = S['area'][0]
    feature5 = S['centroid-0'][0]
    feature6 = S['centroid-1'][0]
    feature7 = S['eccentricity'][0]
    feature8 = S['equivalent_diameter'][0]
    feature9 = S['local_centroid-0'][0]
    feature10 = S['local_centroid-1'][0]
    feature11 = S['major_axis_length'][0]
    feature12 = S['minor_axis_length'][0]
    feature13 = S['orientation'][0]
    feature14 = S['perimeter'][0]
    feature15 = S['solidity'][0]
    
    features = np.array([[feature1,feature2,feature3,feature4,feature5,feature6,feature7,feature8,feature9,feature10,feature11,feature12,feature13,feature14,feature15]])
    return features



# Define the directory containing the images
image_dir = Path(r'C:\Users\savan\OneDrive\Desktop\images-old')
image_path = image_dir


# Create a new Excel file
excel_file = 'image_features.xlsx'
writer = pd.ExcelWriter(excel_file, engine='xlsxwriter')

# Define the columns for the dataframe
columns = ['Image Name', 'Compactness', 'Roundness', 'SF3', 'Area', 'Centroid-0', 'Centroid-1', 'Eccentricity', 'Equivalent_diameter', 'Local_centroid-0', 'Local_centroid-1', 'Major_axis_length', 'Minor_axis_length', 'Orientation', 'Perimeter', 'Solidity']

# Create an empty list to store the dataframes for each image
dfs = []

# Loop over the images and extract their features
for filename in os.listdir(image_dir):
    if filename.endswith('.bmp') or filename.endswith('.jpg') or filename.endswith('.png'):
        # Construct the image path
        image_path = os.path.join(image_dir, filename)
        
        # Extract the features for the current image
        features = extract_features(image_path)
        
        # Construct a new row with the image name and its features
        row = [filename] + features.tolist()[0]
        
        # Create a new dataframe with the row data
        df = pd.DataFrame([row], columns=columns)
        
        # Add the dataframe to the list of dataframes
        dfs.append(df)
        
        
# Concatenate all dataframes into a single one
df = pd.concat(dfs, ignore_index=True)

# Write the dataframe to an Excel file
df.to_excel(writer, sheet_name='Sheet1', index=False)
writer._save()