def write_buffer(self, img, header):
if len(self.frames) >= self.frame_max:
self.frames.pop()
self.headers.pop()
img = imtools.mirror_image(img)
self.frames.append(img)
self.headers.append(header)
def get_images_and_labels(self, path):
import os
image_paths = [os.path.join(path, f) for f in os.listdir(path)]
# images will contains face images
images = []
# labels will contains the label that is assigned to the image
labels = []
for image_path in image_paths:
# Read the image and convert to grayscale
image = cv2.imread(image_path)
# Convert the image format into numpy array
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Get the label of the image
name = os.path.split(image_path)[1].split("_")[0]
self.add_names(name)
labels.append(self.name_id[name])
images.append(image)
# add the mirrored image for training
labels.append(self.name_id[name])
images.append(imtools.mirror_image(image))
print self.name_id
return images, labels
def mirror_image(self, img):
if self.should_mirror:
from imtools import mirror_image
img = mirror_image(img)
return img
