【解決方法】2D バイナリ イメージのボリュームを計算する方法

リンゴ、トマト、レモン、オレンジ、グァバ、グーズベリーのバイナリ イメージの体積、面積、周長、長軸、短軸、離心率を計算する必要があります。 これまでのところ、体積と面積の両方で同じ値が得られると計算されましたが、体積を計算する方法は?

私が試したこと：

import cv2
import pandas as pd
from skimage import measure

# List of binary images
image_list = ["/content/drive/MyDrive/Apple Sample 1/15 1.jpg", "/content/drive/MyDrive/Apple Sample 1/15 2.jpg", "/content/drive/MyDrive/Apple Sample 1/16 1.jpg"]

# Empty list to store extracted features
feature_list = []

# Iterate through the list of images
for image_name in image_list:
    # Read in binary image of apple
    binary_image = cv2.imread(image_name,0)

    # Find contours in the binary image
    contours, _ = cv2.findContours(binary_image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # Extract the first contour
    cnt = contours[0]

    # Calculate the perimeter of the contour
    perimeter = cv2.arcLength(cnt, True)

    # Extract region properties of apple
    regions = measure.regionprops(binary_image)

    # Extract features of interest
    for region in regions:
        volume = region.area
        area = region.area
        eccentricity = region.eccentricity
        major_axis = region.major_axis_length
        minor_axis = region.minor_axis_length

    # Create a dictionary with extracted features
    feature_dict = {"Volume":volume, "Area": area, "Perimeter": perimeter, "Eccentricity": eccentricity, "Major axis": major_axis, "Minor axis": minor_axis}
    # Append the features of each image to the feature_list
    feature_list.append(feature_dict)

# Convert the list of dictionaries to a dataframe
df = pd.DataFrame(feature_list)

# Print the dataframe
print(df)