def get_img(src, img_size=False):
img = imageio.imread(src) # misc.imresize(, (256, 256, 3))
if not (len(img.shape) == 3 and img.shape[2] == 3):
img = np.dstack((img, img, img))
if img_size != False:
img = imageio.imresize(img, img_size)
return img
def compile_frames_to_gif(frame_dir, gif_file):
frames = sorted(glob.glob(os.path.join(frame_dir, "*.png")))
print(frames)
images = [
imageio.imresize(imageio.imread(f), interp='nearest', size=0.33)
for f in frames
]
imageio.imsave(gif_file, images, duration=0.2)
return gif_file
def __call__(self, image, boxes=None, tags=None):
ori_h, ori_w, _ = image.shape
new_image = imageio.imresize(image.copy(), (self.width, self.heigth))
if boxes is not None:
boxes[:, :, 0] *= self.width * 1.0 / ori_w
boxes[:, :, 1] *= self.heigth * 1.0 / ori_h
boxes[:, :, 0] = np.clip(boxes[:, :, 0], 0, self.width)
boxes[:, :, 1] = np.clip(boxes[:, :, 1], 0, self.heigth)
return new_image, boxes, tags
def split(path):
x = []
y = []
count = 0
output = 0
owd = os.getcwd()
os.chdir(path)
for video_class in os.listdir(os.getcwd()):
print(video_class)
gesture = os.listdir(os.path.join(path, video_class))
for class_i in gesture:
sub_child = os.listdir(os.path.join(path, video_class, class_i))
for file in sub_child:
if video_class == 'beer':
if count % 4 == 0:
image = imread(
os.path.join(path, video_class, class_i, file))
image = imresize(image, (224, 224))
x.append(image)
y.append(output)
cv2.imwrite(
os.path.join(path, video_class,
str(count) + '_' + file), image)
else:
if count % 8 == 0:
image = imread(
os.path.join(path, video_class, class_i, file))
image = imresize(image, (224, 224))
x.append(image)
y.append(output)
cv2.imwrite(
path + '/' + video_class + '/' + str(count) + '_' +
file, image)
count += 1
output += 1
x = np.array(x)
y = np.array(y)
print("x", len(x), "y", len(y))
os.chdir(owd)
def save_lip_images(image_path, samples, out_dir):
img_A = imageio.imread(image_path).astype(np.float)
rows = img_A.shape[0]
cols = img_A.shape[1]
image = samples[0]
img_split = image_path.split('/')
img_id = img_split[-1][:-4]
with open('{}/{}.txt'.format(out_dir, img_id), 'w') as f:
for p in range(image.shape[2]):
channel_ = image[:,:,p]
if channel_.shape[0] != rows or channel_.shape[1] != cols:
print ('sizes do not match...')
channel_ = imageio.imresize(channel_, [rows, cols], interp='nearest')
r_, c_ = np.unravel_index(channel_.argmax(), channel_.shape)
f.write('%d %d ' % (int(c_), int(r_)))
def load_image(filename, size=None):
"""Load and resize an image from disk.
Inputs:
- filename: path to file
- size: size of shortest dimension after rescaling
"""
img = imread(filename)
if size is not None:
orig_shape = np.array(img.shape[:2])
min_idx = np.argmin(orig_shape)
scale_factor = float(size) / orig_shape[min_idx]
new_shape = (orig_shape * scale_factor).astype(int)
img = imresize(img, scale_factor)
return img
def _imresize(image_array, size):
return imageio.imresize(image_array, size)
def split(path):
'''
Returns two lists: a list of all images it can find in path,
and their corresponding gesture_folder index.
Resizes all images to 224x224.
Selects every four images in the gesture_folder named "beer"
and every eight in other gestures.
Also writes every four/eight images to some file...
File structure:
- path
- videoclass1
- gesture1
- file{1-100}.jpg # 1 to 100 inclusive
- gesture2
- file{1-100}.jpg
- videoclass2
- ...
Returns:
input_list = [
path/videoclass1/gesture1/file{8,16,24,...,96}.jpg,
path/videoclass1/gesture2/file{4,12,20,...,100}.jpg]
output_list = [
0,0,0,...,0,
1,1,1,...,1]
Writes:
path/videoclass1/gesture1/file{8,16,24,...,96}.jpg -> path/videoclass1/{0,1,2,...,11}_file{8,16,24,...,96}.jpg
path/videoclass1/gesture2/file{4,12,20,...,100}.jpg -> path/videoclass1/{12,13,...,24}_file{4,12,20,...,100}.jpg
'''
input_list = []
output_list = []
count = 0
# Choose path as directory
# rootpath = os.getcwd()
# dataset = os.path.join(os.getcwd(), path)
owd = os.getcwd()
os.chdir(path)
dataset = os.getcwd()
for video_class in os.listdir(dataset):
print(video_class)
gesture_folders = os.listdir(os.path.join(dataset, video_class))
for gesture_index, gesture_folder in enumerate(gesture_folders):
gesture = os.listdir(
os.path.join(dataset, video_class, gesture_folder))
for count, image_filename in enumerate(gesture):
if video_class == 'beer': # Somehow this is a different case...?
if count % 4 == 0:
image = imread(
os.path.join(dataset, video_class, gesture_folder,
image_filename))
image = imresize(image, (224, 224))
input_list.append(image)
output_list.append(gesture_index)
cv2.imwrite(
os.path.join(dataset, video_class,
str(count) + '_' + image_filename),
image)
else:
if count % 8 == 0:
image = imread(
os.path.join(dataset, video_class, gesture_folder,
image_filename))
image = imresize(image, (224, 224))
input_list.append(image)
output_list.append(gesture_index)
cv2.imwrite(
os.path.join(dataset, video_class,
str(count) + '_' + image_filename),
image)
input_list = np.array(input_list)
output_list = np.array(output_list)
os.chdir(owd)
return input_list, output_list