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car_models.py
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car_models.py
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from collections import namedtuple
#--------------------------------------------------------------------------------
# Definitions
#--------------------------------------------------------------------------------
# a label and all meta information
Label = namedtuple('Label', [
'name' , # The name of a car type
'id' , # id for specific car type
'category' , # The name of the car category, 'SUV', 'Sedan' etc
'categoryId' , # The ID of car category. Used to create ground truth images
# on category level.
])
#--------------------------------------------------------------------------------
# A list of all labels
#--------------------------------------------------------------------------------
# Please adapt the train IDs as appropriate for you approach.
# Note that you might want to ignore labels with ID 255 during training.
# Further note that the current train IDs are only a suggestion. You can use whatever you like.
# Make sure to provide your results using the original IDs and not the training IDs.
# Note that many IDs are ignored in evaluation and thus you never need to predict these!
models = [
# name id is_valid category categoryId
Label( 'baojun-310-2017', 0, '2x', 0),
Label( 'biaozhi-3008', 1, '2x', 0),
Label( 'biaozhi-liangxiang', 2, '2x', 0),
Label( 'bieke-yinglang-XT', 3, '2x', 0),
Label( 'biyadi-2x-F0', 4, '2x', 0),
Label( 'changanbenben', 5, '2x', 0),
Label( 'dongfeng-DS5', 6, '2x', 0),
Label( 'feiyate', 7, '2x', 0),
Label( 'fengtian-liangxiang', 8, '2x', 0),
Label( 'fengtian-MPV', 9, '2x', 0),
Label( 'jilixiongmao-2015', 10, '2x', 0),
Label( 'lingmu-aotuo-2009', 11, '2x', 0),
Label( 'lingmu-swift', 12, '2x', 0),
Label( 'lingmu-SX4-2012', 13, '2x', 0),
Label( 'sikeda-jingrui', 14, '2x', 0),
Label( 'fengtian-weichi-2006', 15, '3x', 1),
Label( '037-CAR02', 16, '3x', 1),
Label( 'aodi-a6', 17, '3x', 1),
Label( 'baoma-330', 18, '3x', 1),
Label( 'baoma-530', 19, '3x', 1),
Label( 'baoshijie-paoche', 20, '3x', 1),
Label( 'bentian-fengfan', 21, '3x', 1),
Label( 'biaozhi-408', 22, '3x', 1),
Label( 'biaozhi-508', 23, '3x', 1),
Label( 'bieke-kaiyue', 24, '3x', 1),
Label( 'fute', 25, '3x', 1),
Label( 'haima-3', 26, '3x', 1),
Label( 'kaidilake-CTS', 27, '3x', 1),
Label( 'leikesasi', 28, '3x', 1),
Label( 'mazida-6-2015', 29, '3x', 1),
Label( 'MG-GT-2015', 30, '3x', 1),
Label( 'oubao', 31, '3x', 1),
Label( 'qiya', 32, '3x', 1),
Label( 'rongwei-750', 33, '3x', 1),
Label( 'supai-2016', 34, '3x', 1),
Label( 'xiandai-suonata', 35, '3x', 1),
Label( 'yiqi-benteng-b50', 36, '3x', 1),
Label( 'bieke', 37, '3x', 1),
Label( 'biyadi-F3', 38, '3x', 1),
Label( 'biyadi-qin', 39, '3x', 1),
Label( 'dazhong', 40, '3x', 1),
Label( 'dazhongmaiteng', 41, '3x', 1),
Label( 'dihao-EV', 42, '3x', 1),
Label( 'dongfeng-xuetielong-C6', 43, '3x', 1),
Label( 'dongnan-V3-lingyue-2011', 44, '3x', 1),
Label( 'dongfeng-yulong-naruijie', 45, 'SUV', 2),
Label( '019-SUV', 46, 'SUV', 2),
Label( '036-CAR01', 47, 'SUV', 2),
Label( 'aodi-Q7-SUV', 48, 'SUV', 2),
Label( 'baojun-510', 49, 'SUV', 2),
Label( 'baoma-X5', 50, 'SUV', 2),
Label( 'baoshijie-kayan', 51, 'SUV', 2),
Label( 'beiqi-huansu-H3', 52, 'SUV', 2),
Label( 'benchi-GLK-300', 53, 'SUV', 2),
Label( 'benchi-ML500', 54, 'SUV', 2),
Label( 'fengtian-puladuo-06', 55, 'SUV', 2),
Label( 'fengtian-SUV-gai', 56, 'SUV', 2),
Label( 'guangqi-chuanqi-GS4-2015', 57, 'SUV', 2),
Label( 'jianghuai-ruifeng-S3', 58, 'SUV', 2),
Label( 'jili-boyue', 59, 'SUV', 2),
Label( 'jipu-3', 60, 'SUV', 2),
Label( 'linken-SUV', 61, 'SUV', 2),
Label( 'lufeng-X8', 62, 'SUV', 2),
Label( 'qirui-ruihu', 63, 'SUV', 2),
Label( 'rongwei-RX5', 64, 'SUV', 2),
Label( 'sanling-oulande', 65, 'SUV', 2),
Label( 'sikeda-SUV', 66, 'SUV', 2),
Label( 'Skoda_Fabia-2011', 67, 'SUV', 2),
Label( 'xiandai-i25-2016', 68, 'SUV', 2),
Label( 'yingfeinidi-qx80', 69, 'SUV', 2),
Label( 'yingfeinidi-SUV', 70, 'SUV', 2),
Label( 'benchi-SUR', 71, 'SUV', 2),
Label( 'biyadi-tang', 72, 'SUV', 2),
Label( 'changan-CS35-2012', 73, 'SUV', 2),
Label( 'changan-cs5', 74, 'SUV', 2),
Label( 'changcheng-H6-2016', 75, 'SUV', 2),
Label( 'dazhong-SUV', 76, 'SUV', 2),
Label( 'dongfeng-fengguang-S560', 77, 'SUV', 2),
Label( 'dongfeng-fengxing-SX6', 78, 'SUV', 2)
]
#--------------------------------------------------------------------------------
# Create dictionaries for a fast lookup
#--------------------------------------------------------------------------------
# Please refer to the main method below for example usages!
# name to label object
car_name2id = {label.name: label for label in models}
car_id2name = {label.id: label for label in models}
# if __name__ == '__main__':
# print(car_id2name[0].name)