def _aug(self, image, mask):
mask = SegmentationMapsOnImage(mask, image.shape[:2])
seq = iaa.Sequential(
[
iaa.Fliplr(0.5),
iaa.Rot90([0, 3]),
iaa.SomeOf(
1,
[
iaa.Affine(scale={
"x": (0.7, 1.5),
"y": (1.6, 1.5)
}),
iaa.Affine(rotate=(-30, 30)),
# iaa.Add((-110, 111)),
# iaa.GaussianBlur(sigma=1.8 * np.random.rand()),
# iaa.Emboss(alpha=(0.0, 1.0), strength=(0.5, 1.5)),
# iaa.AdditiveGaussianNoise(scale=0.05*255),
# iaa.Multiply((0.5, 1.5)),
# iaa.Affine(shear=(-20, 20)),
# iaa.PiecewiseAffine(scale=(0.01, 0.02)),
iaa.PerspectiveTransform(scale=(0.01, 0.1)),
],
),
],
random_order=True,
)
image, mask = seq(image=image, segmentation_maps=mask)
mask = mask.get_arr_int().astype(np.uint8)
return image, mask
def load_batch_pair_in_pair(self, img_paths, label_paths):
images = []
segs = []
preprocessors = [self.resize_img, self.mean_substraction]
for i in range(len(img_paths)):
image = self.load_image(img_paths[i])
# image = self.preprocessing(image, preprocessors)
seg = self.load_image(label_paths[i])
# seg = self.preprocessing(seg, [self.resize_img])
# print(seg.dtype)
# seg = seg.astype(np.uint8)
# seg = self.parse_label(seg)
# seg = np.argmax(seg, axis=-1).astype(np.int32)
segmap = SegmentationMapsOnImage(seg[:, :, 0],
shape=image.shape,
nb_classes=np.max(seg[:, :, 0]) +
1)
if self.augmentation:
image, segmap = self.augment_func(image=image,
segmentation_maps=segmap)
seg[:, :, 0] = segmap.get_arr_int()
image = self.preprocessing(image, preprocessors)
# seg = self.preprocessing(seg, [self.resize_img])
seg = self.resize_img(seg, interpolation=cv2.INTER_NEAREST)
seg = seg / 255
seg[seg > 0.5] = 1
seg[seg <= 0.5] = 0
seg = self.parse_label(seg)
images.append(image)
segs.append(seg)
return np.array(images), np.array(segs)
def make_json(masks_dir, masks_list, img_dir, class_name, dataset_dir):
with open("template.json") as json_file:
template = json.load(json_file)
for mask in masks_list:
mask_path = os.path.join(masks_dir, '0' + mask[0], mask)
image_name = mask.split('_')[0]
new_shape = {}
new_shape['label'] = class_name
new_shape['line_color'] = None
new_shape['fill_color'] = None
new_shape['shape_type'] = "polygon"
new_shape['flags'] = {}
real_image = Image.open(
os.path.join(dataset_dir, img_dir, class_name,
image_name + '.jpg'))
real_width, real_height = real_image.size
mask_image = Image.open(mask_path)
width, height = mask_image.size
mask_array = np.array(mask_image)
mask_array = SegmentationMapsOnImage(mask_array,
(height, width)).resize(
(real_height, real_width))
segmap_aug_arr = np.array(
mask_array.get_arr_int(background_threshold=0 + .1))
segmap_single = np.ma.masked_where(
True, segmap_aug_arr).mask * segmap_aug_arr
polygons = Mask(segmap_single).polygons()
# Image.fromarray(mask_array.draw_on_image(np.array(real_image))[0]).show()
if len(polygons.points) > 1:
selected_points = polygons.points[0]
for points in polygons.points:
if selected_points.size < points.size:
selected_points = points
new_shape['points'] = np.array(selected_points).tolist()
else:
try:
new_shape['points'] = np.array(polygons.points).tolist()[0]
except:
new_shape['points'] = np.array(polygons.points).tolist()
json_file_path = os.path.join(dataset_dir, img_dir, class_name,
image_name + '.json')
if os.path.exists(json_file_path):
existing_json = None
with open(json_file_path) as preexisting_json:
existing_json = json.load(preexisting_json)
for old_shapes in existing_json['shapes']:
template['shapes'].append(old_shapes)
template['flags']["multiple targets"] = True
template['imagePath'] = image_name + '.jpg'
template['imageHeight'] = existing_json['imageHeight']
template['imageWidth'] = existing_json['imageWidth']
template['shapes'].append(new_shape)
template['imagePath'] = image_name + '.jpg'
template['imageHeight'] = real_height
template['imageWidth'] = real_width
template['imageData'] = None
with open(json_file_path, 'w+') as outfile:
json.dump(template, outfile, indent=2)
new_mask_path = os.path.join(dataset_dir, img_dir, class_name, mask)
shutil.copy(mask_path, new_mask_path)
template['shapes'] = []
