help="data type [train, valid]",
choices=["train", "valid"])
parser.add_argument(
"-c",
"--category",
help="category type [date, number, all]",
choices=["date", "number", "all"],
default="all",
)
parser.add_argument("-o",
"--output",
help="save result file path",
default="results")
args = parser.parse_args()
images, anns, classes = loadAnns(args.basedir, args.target)
assert len(classes) == 11, "all data annotation set should be needed"
if args.category == "date":
allowcatnum = [11]
classes = [classes[10]]
classes[0]["id"] = 1
elif args.category == "number":
allowcatnum = list(range(1, 11))
classes = classes[0:10]
new_anns = []
if args.category != "all":
for ann in anns:
if ann["category_id"] in allowcatnum:
if args.category == "date":
required=True)
parser.add_argument("-n",
"--name",
help="append name for replace image",
default="d3")
parser.add_argument("-t",
"--target",
help="data type [train, valid]",
choices=["train", "valid"])
parser.add_argument("-o",
"--output",
help="save result file path",
default="results")
args = parser.parse_args()
images0, anns0, classes0 = loadAnns(args.dataset0, args.target)
images1, anns1, classes1 = loadAnns(args.dataset1, args.target)
assert classes0 == classes1, "two dataset has different classes"
imagename2imgidx = {}
for idx, image1 in enumerate(images1):
imagename2imgidx[image1["file_name"]] = idx
imageid2annidx = {}
for idx, ann1 in enumerate(anns1):
if ann1["image_id"] not in imageid2annidx:
imageid2annidx[ann1["image_id"]] = []
imageid2annidx[ann1["image_id"]].append(idx)
os.makedirs(os.path.join(args.output, args.target), exist_ok=True)
"-o", "--output", help="save result file path", default="results"
)
args = parser.parse_args()
basedir = os.path.abspath(os.path.expanduser(args.basedir))
imageSizes = [(2480, 3507), (793, 1121)]
std_size = (793, 1121)
convertRate = {}
for size in imageSizes:
assert size[0] != 0 and size[1] != 0, "size should not be zero"
convertRate[size[0]] = std_size[0] / size[0]
for target in args.targets:
imageAnns, Anns, categories = loadAnns(basedir, target)
idlist = {}
os.makedirs(os.path.join(args.output, target), exist_ok=True)
for imageann in tqdm(imageAnns, desc=f"{target} : "):
idlist[imageann["id"]] = convertRate[imageann["width"]]
imageann["height"] = int(
imageann["height"] * convertRate[imageann["width"]] + 0.5
)
imageann["width"] = int(
imageann["width"] * convertRate[imageann["width"]] + 0.5
)
img = cv2.imread(os.path.join(basedir, target, imageann["file_name"]))
img = cv2.resize(img, (imageann["width"], imageann["height"]))
for m in [(0, 3, 3, 6), (3, 6, 0, 3)]:
for j in range(m[0], m[1]):
move = -args.gap * 3
for k in range(0, 2):
for i in range(m[2], m[3]):
copymethod.append([i, j, move])
if move == -args.gap:
move += args.gap * 2
else:
move += args.gap
os.makedirs(os.path.join(args.outdir, args.target), exist_ok=True)
images, annotations, categories = loadAnns(datapath, args.target)
imageid2ann = {}
for ann in annotations:
if ann["image_id"] not in imageid2ann:
imageid2ann[ann["image_id"]] = []
imageid2ann[ann["image_id"]].append(ann)
'''
sorted datebox
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