- Here in this img_path path you have to replaced with your path
- In this Project Create two files One for Extracting Features from Image
- another Excel_conversion.py to Extract Features from Extracted festures to Convert into excel
- Here you will get live Example Converted Features into Excel that image_features.xlsx
FeatureExtraction:
Documentation:
This is a Python script that defines a function named ShapeSizeFeature which takes a grayscale thresholded image as input and returns a dictionary of shape and size features of objects in the input image.
The script uses the following libraries:
cv2(OpenCV): for computer vision and image processing functions.numpy(Numerical Python): for numerical operations and array manipulations.skimage(Scikit-Image): for image processing and analysis functions.
The ShapeSizeFeature function takes a single argument thresh, which is a thresholded image, i.e., a binary image where white pixels represent objects of interest and black pixels represent the background. The function first labels the objects in the input image using the label function from Scikit-Image. The label function assigns a unique integer label to each connected component in the input image.
The function then uses the regionprops_table function from Scikit-Image to compute various shape and size features of the labeled objects. The function computes the following features for each object:
- area: the number of pixels in the object.
- perimeter: the perimeter length of the object.
- major_axis_length: the length of the major axis of the ellipse that best fits the object.
- minor_axis_length: the length of the minor axis of the ellipse that best fits the object.
- centroid: the centroid (center of mass) of the object.
- local_centroid: the centroid of the object relative to its bounding box.
- coords: the coordinates of all pixels in the object.
- eccentricity: the eccentricity of the ellipse that best fits the object.
- equivalent_diameter: the diameter of a circle with the same area as the object.
- orientation: the angle between the major axis of the object and the x-axis.
- solidity: the ratio of the object's area to the area of its convex hull.
The function then computes three additional features based on the above properties:
- Roundness: a measure of how closely an object resembles a circle, defined as
(4 * pi * area) / (perimeter^2). - Compactness: a measure of how compact an object is, defined as
sqrt((4 * area) / pi) / major_axis_length. - SF3: a measure of how elongated an object is, defined as
area / ((major_axis_length/2) * (minor_axis_length/2) * pi).
The function returns a dictionary props containing all the computed features, along with their corresponding values for each labeled object in the input image.