How to reduce extract image feature time?

Python
1

Hi everyone,
I have just learned about computer vision. Currently, i am processing a problem about image classification. I used HoG to extract features from images, but it takes a very long time whenever i run it. Is there anyway to reduce the time run it because my dataset is very large (about 15k images). And HoG extracts an image into a (1, 16740) vector dimension.
Here is the code i uses to extract features:

def calc_hog(imgPath):
    img = cv2.imread(imgPath)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    resized_img = cv2.resize(img, (256, 128))
    features, hog_image = hog(resized_img, orientations=9, pixels_per_cell=(8, 8),
                              cells_per_block=(2, 2), visualize=True, channel_axis=-1)
    return features

I am very thankful that you guys read my question, and i hope i can receive an answer soon.
Regard.

Edited:
This is the code which i use to load images:

def loadDataset(imgPath, dataf, features_extraction):
    x = []
    y = []

    sto = dataf.reset_index(drop=True)

    for i in range(len(sto)):
        img_path = os.path.join(imgPath, sto['image'][i])
        x.append(features_extraction(img_path))
        y.append(dataf['label'][i])

    x = np.array(x)
    y = np.array(y)

    return x, y
2

please find out how much time each line in your code takes. sum up the individual times per line across the entire dataset. use time.perf_counter(), or use a proper profiler

1 Like
3

It’s about 4683s (1 hour 18 minutes) for 12271 images to make a (12271, 16740) matrix from using HoG. And i still have 3k images more to run :frowning:.

4

i don’t mean the grand total.

I mean you need to find out which line in calc_hog takes how long.

1 Like
6

this should be a one-time, offline task.

.gather your hog features once & serialize for later use

7

Great!

So that looks like… twenty nine seconds (29 s) to merely read the image, and another 0.3 secs for the actual processing, the majority of which is the hog() call.

now I don’t know how hog is defined. you didn’t show that code. for all I know, it’s not even from OpenCV but from skimage

could you provide details on that?

8

yes, you are right, that hog is come from skimage. I dont know clearly how it’s work but they provided it in this documentation Histogram of Oriented Gradients — skimage 0.23.2 documentation (scikit-image.org) and this scikit-image/skimage/feature/_hog.py at main · scikit-image/scikit-image · GitHub.
By the way as berak say, can you suggest me a keyword or something so that i can findout way to do this once (i wonder if the time i load is more faster than process it for each time run).

9

it’s just a numpy array, so you can use any method to store and load numpy arrays

1 Like