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