def __call__(self, results):
img = results['img']
orig_type = img.dtype
anns = self._load_anns(results)
aaa = len(anns)
bbb = anns.copy()
if np.random.choice([0, 1], p=[1 - self.aug_ratio, self.aug_ratio]):
try:
import instaboostfast as instaboost
except ImportError:
raise ImportError('Please run "pip install instaboostfast" '
'to install instaboostfast first.')
anns, img = instaboost.get_new_data(anns,
img.astype(np.uint8),
self.cfg,
background=None)
####################
#if len(anns) != aaa:
#ccc = len(results['ann_info']['bboxes'])
# if len(results['ann_info']['bboxes'])==0:
# print(results['img_info'])
# for ann in anns:
# print(ann['bbox']) # clw modify
# print()
# for ann in bbb:
# print(ann['bbox'])
# results['ann_info']['bboxes'] = np.empty([0, 4], dtype=np.float32) # clw modify: fix bug of empty gt
######################
results = self._parse_anns(results, anns, img.astype(orig_type))
return results
def __call__(self, results):
img = results['img']
anns = self._load_anns(results)
if np.random.choice([0, 1], p=[1 - self.aug_ratio, self.aug_ratio]):
try:
import instaboostfast as instaboost
except ImportError:
raise ImportError('Please run "pip install instaboostfast" '
'to install instaboostfast first.')
anns, img = instaboost.get_new_data(
anns, img, self.cfg, background=None)
results = self._parse_anns(results, anns, img)
return results
def boost(img, target, img_id):
anns = []
height, width, channels = img.shape
ori_target = deepcopy(target)
try:
for id in range(len(target)):
item = target[id]
ann = {}
ann['bbox'] = [
item[0] * width, item[1] * height, (item[2] - item[0]) * width,
(item[3] - item[1]) * height
]
ann['segmentation'] = find_seg(img_id, item[:4])
if not ann['segmentation']:
continue
ann['category_id'] = id
anns.append(ann)
# print("t1",time.time()-t0)
new_anns, new_img = get_new_data(
anns, img, config=InstaBoostConfig(heatmap_flag=True))
# print("t2",time.time()-t0)
for id in range(len(target)):
for ann in new_anns:
if id == ann['category_id']:
target[id][0] = ann['bbox'][0] / float(width)
target[id][1] = ann['bbox'][1] / float(height)
target[id][2] = (ann['bbox'][0] +
ann['bbox'][2]) / float(width)
target[id][3] = (ann['bbox'][1] +
ann['bbox'][3]) / float(height)
# print("t3",time.time()-t0)
except:
target = ori_target
new_img = img
# r = random.randint(1,10000)
# cv2.imwrite("image/%d_ori.png"%r,img)
# cv2.imwrite("image/%d_new.png"%r,new_img)
return new_img, target