def augment(self, image, bboxes):
image, bboxes = random_augmentations(image, self.augmentation_config, bboxes=bboxes)
image, bboxes = random_function_bboxes(image, bboxes, random_pad_to_square, 0.3)
# unfortunately we are still missing some augmentations in tf_image
image = random_function(image, tf_py_contrast, prob=0.3)
image = random_function(image, tf_py_blur, prob=0.3)
image = random_function(image, tf_py_dropout, prob=0.3)
return image, bboxes
for o in soup.find_all("object"):
xMin = int(o.find("xmin").string)
yMin = int(o.find("ymin").string)
xMax = int(o.find("xmax").string)
yMax = int(o.find("ymax").string)
bboxes.append([yMin, xMin, yMax, xMax])
bboxes = np.array(bboxes, dtype=np.float32)
# original bbox in relative coordinates [0...1]
bboxes /= np.stack([h, w, h, w])
for t in range(config.NUM_AUG):
image_augmented, bboxes_augmented = random_augmentations(
image,
aug_config,
bboxes=tf.constant(bboxes)
)
image_augmented_encoded = tf.image.encode_png(image_augmented)
FILENAME_AUG = '{}_aug_{}.jpg'.format(filename, t)
tf.io.write_file(os.path.sep.join([config.TRAIN_SET,
FILENAME_AUG]),
image_augmented_encoded)
# augmented bbox to absolute coordinates
bboxes_abs = ((bboxes_augmented.numpy() *
np.stack([tf.shape(image_augmented)[0],
tf.shape(image_augmented)[1],
def augment(self, image, bboxes):
return random_augmentations(image, self.augmentation_config, bboxes=bboxes)
image = tf.image.decode_jpeg(image_encoded)
bboxes = tf.constant([[262.0, 135.0, 504.0,
371.0], [285.0, 446.0, 494.0, 644.0],
[272.0, 688.0, 493.0, 895.0]])
bboxes /= tf.cast(
tf.stack([
tf.shape(image)[0],
tf.shape(image)[1],
tf.shape(image)[0],
tf.shape(image)[1],
]), tf.float32)
bboxes_colors = [[0, 0, 255], [0, 0, 255], [0, 0, 255]]
for i in range(3):
image_augmented = random_augmentations(image, config)
image_augmented_encoded = tf.image.encode_png(image_augmented)
tf.io.write_file(f"images/results/ximilar-similar_{i + 1}.png",
image_augmented_encoded)
for i in range(3):
image_augmented, bboxes_augmented = random_augmentations(image,
config,
bboxes=bboxes)
image_augmented = tf.image.draw_bounding_boxes([image_augmented],
[bboxes_augmented],
bboxes_colors)[0]
image_augmented = tf.cast(
image_augmented, tf.uint8