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path: ../datasets/coco # dataset root dir | |
train: train2017.txt # train images (relative to 'path') 118287 images | |
val: val2017.txt # val images (relative to 'path') 5000 images | |
test: test-dev2017.txt # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794 | |
# Classes | |
names: | |
0: person | |
1: bicycle | |
2: car | |
3: motorcycle | |
4: airplane | |
5: bus | |
6: train | |
7: truck | |
8: boat | |
9: traffic light | |
10: fire hydrant | |
11: stop sign | |
12: parking meter | |
13: bench | |
14: bird | |
15: cat | |
16: dog | |
17: horse | |
18: sheep | |
19: cow | |
20: elephant | |
21: bear | |
22: zebra | |
23: giraffe | |
24: backpack | |
25: umbrella | |
26: handbag | |
27: tie | |
28: suitcase | |
29: frisbee | |
30: skis | |
31: snowboard | |
32: sports ball | |
33: kite | |
34: baseball bat | |
35: baseball glove | |
36: skateboard | |
37: surfboard | |
38: tennis racket | |
39: bottle | |
40: wine glass | |
41: cup | |
42: fork | |
43: knife | |
44: spoon | |
45: bowl | |
46: banana | |
47: apple | |
48: sandwich | |
49: orange | |
50: broccoli | |
51: carrot | |
52: hot dog | |
53: pizza | |
54: donut | |
55: cake | |
56: chair | |
57: couch | |
58: potted plant | |
59: bed | |
60: dining table | |
61: toilet | |
62: tv | |
63: laptop | |
64: mouse | |
65: remote | |
66: keyboard | |
67: cell phone | |
68: microwave | |
69: oven | |
70: toaster | |
71: sink | |
72: refrigerator | |
73: book | |
74: clock | |
75: vase | |
76: scissors | |
77: teddy bear | |
78: hair drier | |
79: toothbrush | |
# stuff names | |
stuff_names: [ | |
'banner', 'blanket', 'branch', 'bridge', 'building-other', 'bush', 'cabinet', 'cage', | |
'cardboard', 'carpet', 'ceiling-other', 'ceiling-tile', 'cloth', 'clothes', 'clouds', 'counter', 'cupboard', | |
'curtain', 'desk-stuff', 'dirt', 'door-stuff', 'fence', 'floor-marble', 'floor-other', 'floor-stone', 'floor-tile', | |
'floor-wood', 'flower', 'fog', 'food-other', 'fruit', 'furniture-other', 'grass', 'gravel', 'ground-other', 'hill', | |
'house', 'leaves', 'light', 'mat', 'metal', 'mirror-stuff', 'moss', 'mountain', 'mud', 'napkin', 'net', 'paper', | |
'pavement', 'pillow', 'plant-other', 'plastic', 'platform', 'playingfield', 'railing', 'railroad', 'river', 'road', | |
'rock', 'roof', 'rug', 'salad', 'sand', 'sea', 'shelf', 'sky-other', 'skyscraper', 'snow', 'solid-other', 'stairs', | |
'stone', 'straw', 'structural-other', 'table', 'tent', 'textile-other', 'towel', 'tree', 'vegetable', 'wall-brick', | |
'wall-concrete', 'wall-other', 'wall-panel', 'wall-stone', 'wall-tile', 'wall-wood', 'water-other', 'waterdrops', | |
'window-blind', 'window-other', 'wood', | |
# other | |
'other', | |
# unlabeled | |
'unlabeled' | |
] | |
# Download script/URL (optional) | |
download: | | |
from utils.general import download, Path | |
# Download labels | |
#segments = True # segment or box labels | |
#dir = Path(yaml['path']) # dataset root dir | |
#url = 'https://github.com/WongKinYiu/yolov7/releases/download/v0.1/' | |
#urls = [url + ('coco2017labels-segments.zip' if segments else 'coco2017labels.zip')] # labels | |
#download(urls, dir=dir.parent) | |
# Download data | |
#urls = ['http://images.cocodataset.org/zips/train2017.zip', # 19G, 118k images | |
# 'http://images.cocodataset.org/zips/val2017.zip', # 1G, 5k images | |
# 'http://images.cocodataset.org/zips/test2017.zip'] # 7G, 41k images (optional) | |
#download(urls, dir=dir / 'images', threads=3) | |