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| import sys | |
| import dlib | |
| from skimage import io | |
| # Take the image file name from the command line | |
| file_name = sys.argv[1] | |
| # Create a HOG face detector using the built-in dlib class | |
| face_detector = dlib.get_frontal_face_detector() | |
| win = dlib.image_window() | |
| # Load the image into an array | |
| image = io.imread(file_name) | |
| # Run the HOG face detector on the image data. | |
| # The result will be the bounding boxes of the faces in our image. | |
| detected_faces = face_detector(image, 1) | |
| print("I found {} faces in the file {}".format(len(detected_faces), file_name)) | |
| # Open a window on the desktop showing the image | |
| win.set_image(image) | |
| # Loop through each face we found in the image | |
| for i, face_rect in enumerate(detected_faces): | |
| # Detected faces are returned as an object with the coordinates | |
| # of the top, left, right and bottom edges | |
| print("- Face #{} found at Left: {} Top: {} Right: {} Bottom: {}".format(i, face_rect.left(), face_rect.top(), face_rect.right(), face_rect.bottom())) | |
| # Draw a box around each face we found | |
| win.add_overlay(face_rect) | |
| # Wait until the user hits <enter> to close the window | |
| dlib.hit_enter_to_continue() |
Hey I got "module 'dlib' has no attribute 'image_window'" and I followed https://gist.github.com/ageitgey/629d75c1baac34dfa5ca2a1928a7aeaf to install dlib. using mac 10.12.6. Do you have any idea what I did wrong?
You can uninstall dlib absolutely, and install the dlib again.(If this can't help you, you can install the other version to try it)
Its not working for all images ,only faces from particular images of human are being detected
How can I connect this to webcam so that it can detect my face?
If you're using OpenCV use this function
import cv2
v1 = cv2.VideoCapture(0) # 0 -- indicates your webcam
print(v1.isOpened()) # Returns bool value based on the video capture object
I have successfully run this script and it return an image with a box in face. But I just want a HOG image just like that:
How can I get it?
from skimage.feature import hog
from skimage import exposure
import cv2
image = cv2.imread('/your/image/path')
fd, hog_image = hog(image, orientations=8, pixels_per_cell=(16, 16),
cells_per_block=(1, 1), visualize=True, multichannel=True)
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4), sharex=True, sharey=True)
ax1.axis('off')
ax1.imshow(image, cmap=plt.cm.gray)
ax1.set_title('Input image')
# Rescale histogram for better display
hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, 10))
ax2.axis('off')
ax2.imshow(hog_image_rescaled, cmap=plt.cm.gray)
ax2.set_title('Histogram of Oriented Gradients')
plt.show()
from skimage.feature import hog from skimage import exposure import cv2 image = cv2.imread('/your/image/path') fd, hog_image = hog(image, orientations=8, pixels_per_cell=(16, 16), cells_per_block=(1, 1), visualize=True, multichannel=True) fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4), sharex=True, sharey=True) ax1.axis('off') ax1.imshow(image, cmap=plt.cm.gray) ax1.set_title('Input image') # Rescale histogram for better display hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, 10)) ax2.axis('off') ax2.imshow(hog_image_rescaled, cmap=plt.cm.gray) ax2.set_title('Histogram of Oriented Gradients') plt.show()
Hi, you forgot to add: "from matplotlib import pyplot as plt".
@Dankrou yeah it was on a different kernel but thanks for pointing that out.
import os
import sys
import dlib
from skimage import io, exposure
from skimage.feature import hog
import cv2
import matplotlib.pyplot as plt
main = os.path.abspath(sys.argv[0])
file_name = os.path.abspath(os.path.join(os.path.dirname(main), "examples","faces","2.jpg"))
Contruye histograma de un rostros para identificación
image = cv2.imread(file_name)
fd, hog_image = hog(image, orientations=8, pixels_per_cell=(16, 16),
cells_per_block=(1, 1), visualize=True, channel_axis=2)
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4), sharex=True, sharey=True)
ax1.axis('off')
ax1.imshow(image, cmap=plt.cm.gray)
ax1.set_title('Input image')
Rescale histogram for better display
hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, 20))
ax2.axis('off')
ax2.imshow(hog_image_rescaled, cmap=plt.cm.gray)
ax2.set_title('Histogram of Oriented Gradients')
plt.show()
Do you know how to show HOG fetures?