def main(config):
if config["datasets"] == "VOC":
voc = VOC()
yolo = YOLO(os.path.abspath(config["cls_list"]))
flag, data = voc.parse(config["label"])
if flag == True:
flag, data = yolo.generate(data)
if flag == True:
flag, data = yolo.save(data, config["output_path"], config["img_path"] ,
config["img_type"], config["records_path"])
if flag == False:
print("Saving Result : {}, msg : {}".format(flag, data))
else:
print("YOLO Generating Result : {}, msg : {}".format(flag, data))
else:
print("VOC Parsing Result : {}, msg : {}".format(flag, data))
elif config["datasets"] == "COCO":
coco = COCO()
yolo = YOLO(os.path.abspath(config["cls_list"]))
flag, data = coco.parse(config["label"])
if flag == True:
flag, data = yolo.generate(data)
if flag == True:
flag, data = yolo.save(data, config["output_path"], config["img_path"],
config["img_type"], config["records_path"])
if flag == False:
print("Saving Result : {}, msg : {}".format(flag, data))
else:
print("YOLO Generating Result : {}, msg : {}".format(flag, data))
else:
print("COCO Parsing Result : {}, msg : {}".format(flag, data))
else:
print("Unkwon Datasets")
def main(config):
if config["datasets"] == "VOC":
voc = VOC()
yolo = YOLO(os.path.abspath(config["cls_list"]))
flag, data = voc.parse(config["label"])
if flag == True:
flag, data = yolo.generate(data)
if flag == True:
flag, data = yolo.save(data, config["output_path"],
config["img_path"], config["img_type"],
config["manifest_path"])
if flag == False:
print("Saving Result : {}, msg : {}".format(flag, data))
else:
print("YOLO Generating Result : {}, msg : {}".format(
flag, data))
else:
print("VOC Parsing Result : {}, msg : {}".format(flag, data))
elif config["datasets"] == "COCO":
coco = COCO()
keep = {
"person", "bicycle", "car", "motorcycle", "bus", "train", "truck"
}
flag, data, cls_hierarchy = coco.parse(config["label"],
config["img_path"],
keep=keep)
data = sampleDataset(data, config["num_samples"], keep, config["seed"])
yolo = YOLO(os.path.abspath(config["cls_list"]),
cls_hierarchy=cls_hierarchy)
if flag == True:
flag, data = yolo.generate(data)
if flag == True:
flag, data = yolo.save(data, config["output_path"],
config["img_path"], config["img_type"],
config["manifest_path"])
if flag == False:
print("Saving Result : {}, msg : {}".format(flag, data))
else:
print("YOLO Generating Result : {}, msg : {}".format(
flag, data))
else:
print("COCO Parsing Result : {}, msg : {}".format(flag, data))
elif config["datasets"] == "UDACITY":
udacity = UDACITY()
yolo = YOLO(os.path.abspath(config["cls_list"]))
flag, data = udacity.parse(config["label"])
if flag == True:
flag, data = yolo.generate(data)
if flag == True:
flag, data = yolo.save(data, config["output_path"],
config["img_path"], config["img_type"],
config["manifest_path"])
if flag == False:
print("Saving Result : {}, msg : {}".format(flag, data))
else:
print("UDACITY Generating Result : {}, msg : {}".format(
flag, data))
else:
print("COCO Parsing Result : {}, msg : {}".format(flag, data))
elif config["datasets"] == "KITTI":
kitti = KITTI()
yolo = YOLO(os.path.abspath(config["cls_list"]))
flag, data = kitti.parse(config["label"],
config["img_path"],
img_type=config["img_type"])
if flag == True:
flag, data = yolo.generate(data)
if flag == True:
flag, data = yolo.save(data, config["output_path"],
config["img_path"], config["img_type"],
config["manifest_path"])
if flag == False:
print("Saving Result : {}, msg : {}".format(flag, data))
else:
print("YOLO Generating Result : {}, msg : {}".format(
flag, data))
else:
print("KITTI Parsing Result : {}, msg : {}".format(flag, data))
else:
print("Unkwon Datasets")