花卉识别分割数据集labelme格式7111张102类别
花卉识别分割数据集labelme格式7111张102类别
git clone firc-dataset
发布于 2025-07-17 19:38:56
发布于 2025-07-17 19:38:56
数据集格式：labelme格式(不包含mask文件，仅仅包含jpg图片和对应的json文件)
图片数量(jpg文件个数)：7111
标注数量(json文件个数)：7111
标注类别数：102
标注类别名称:["stemless_gentian","peruvian_lily","bougainvillea","bromelia","californian_poppy","giant_white_arum_lily","camellia","canna_lily","canterbury_bells","cape_flower","carnation","cautleya_spicata","tiger_lily","clematis","anthurium","colts_foot","columbine","common_dandelion","corn_poppy","mexican_aster","siam_tulip","cyclamen","moon_orchid","desert-rose","balloon_flower","purple_coneflower","foxglove","oxeye_daisy","frangipani","artichoke","fritillary","gaura","gazania","geranium","bird_of_paradise","snapdragon","english_marigold","globe_flower","globe_thistle","fire_lily","great_masterwort","azalea","hard-leaved_pocket_orchid","hibiscus","hippeastrum","japanese_anemone","lenten_rose","lotus","magnolia","mallow","marigold","mexican_petunia","buttercup","monkshood","ball_moss","morning_glory","grape_hyacinth","love_in_the_mist","yellow_iris","orange_dahlia","osteospermum","passion_flower","barbeton_daisy","pelargonium","petunia","pincushion_flower","pink-yellow_dahlia","pink_primrose","poinsettia","primula","prince_of_wales_feathers","garden_phlox","red_ginger","rose","ruby-lipped_cattleya","silverbush","bearded_iris","spear_thistle","spring_crocus","sunflower","daffodil","sweet_william","sweet_pea","sword_lily","alpine_sea_holly","thorn_apple","bee_balm","toad_lily","tree_mallow","tree_poppy","trumpet_creeper","wallflower","watercress","bishop_of_llandaff","water_lily","wild_pansy","windflower","king_protea","black_eyed_susan","blackberry_lily","blanket_flower","bolero_deep_blue"]
每个类别标注的框数：
stemless_gentian count = 103
peruvian_lily count = 112
bougainvillea count = 143
bromelia count = 58
californian_poppy count = 102
giant_white_arum_lily count = 62
camellia count = 83
canna_lily count = 129
canterbury_bells count = 97
cape_flower count = 166
carnation count = 68
cautleya_spicata count = 55
tiger_lily count = 36
clematis count = 115
anthurium count = 133
colts_foot count = 122
columbine count = 84
common_dandelion count = 88
corn_poppy count = 39
mexican_aster count = 35
siam_tulip count = 37
cyclamen count = 266
moon_orchid count = 72
desert-rose count = 127
balloon_flower count = 65
purple_coneflower count = 100
foxglove count = 215
oxeye_daisy count = 52
frangipani count = 169
artichoke count = 85
fritillary count = 97
gaura count = 95
gazania count = 103
geranium count = 116
bird_of_paradise count = 80
snapdragon count = 87
english_marigold count = 69
globe_flower count = 52
globe_thistle count = 46
fire_lily count = 45
great_masterwort count = 111
azalea count = 129
hard-leaved_pocket_orchid count = 58
hibiscus count = 136
hippeastrum count = 136
japanese_anemone count = 72
lenten_rose count = 66
lotus count = 127
magnolia count = 80
mallow count = 80
marigold count = 140
mexican_petunia count = 124
buttercup count = 64
monkshood count = 214
ball_moss count = 47
morning_glory count = 121
grape_hyacinth count = 46
love_in_the_mist count = 48
yellow_iris count = 45
orange_dahlia count = 70
osteospermum count = 96
passion_flower count = 236
barbeton_daisy count = 139
pelargonium count = 72
petunia count = 265
pincushion_flower count = 63
pink-yellow_dahlia count = 190
pink_primrose count = 123
poinsettia count = 106
primula count = 207
prince_of_wales_feathers count = 122
garden_phlox count = 168
red_ginger count = 43
rose count = 166
ruby-lipped_cattleya count = 135
silverbush count = 61
bearded_iris count = 52
spear_thistle count = 44
spring_crocus count = 56
sunflower count = 56
daffodil count = 73
sweet_william count = 212
sweet_pea count = 156
sword_lily count = 196
alpine_sea_holly count = 56
thorn_apple count = 114
bee_balm count = 58
toad_lily count = 47
tree_mallow count = 86
tree_poppy count = 65
trumpet_creeper count = 111
wallflower count = 201
watercress count = 206
bishop_of_llandaff count = 148
water_lily count = 199
wild_pansy count = 90
windflower count = 56
king_protea count = 50
black_eyed_susan count = 53
blackberry_lily count = 55
blanket_flower count = 48
bolero_deep_blue count = 49
使用标注工具：labelme=5.5.0
标注规则：对类别进行画多边形框polygon
重要说明：可以将数据集用labelme打开编辑，json数据集需自己转成mask或者yolo格式或者coco格式作语义分割或者实例分割
特别声明：本数据集不对训练的模型或者权重文件精度作任何保证，数据集只提供准确且合理标注
图片预览：
标注例子：
【labelme格式说明】
labelme格式就是一种json文件里面特定存储格式，示例如下：
{
"version": "5.5.0",
"flags": {},
"shapes": [
{
"label": "snapdragon",
"points": [
[
543.5,
472
],
[
539,
475.5
],
[
540,
455.5
],
[
543.5,
468
],
[
545,
459.5
],
[
549,
457.5
],
[
545,
449.5
],
[
553,
434.5
],
[
561.5,
428
],
[
587.5,
428
],
[
598.5,
422
],
[
600,
413.5
],
[
611,
398.5
],
[
606,
378.5
],
[
616,
362.5
],
[
606,
352.5
],
[
605,
345.5
],
[
614,
322.5
],
[
620,
286.5
],
[
610,
273.5
],
[
609,
234.5
],
[
589.5,
216
],
[
566.5,
206
],
[
544.5,
209
],
[
515.5,
239
],
[
502,
232.5
],
[
510,
214.5
],
[
529,
201.5
],
[
529,
180.5
],
[
520.5,
168
],
[
498.5,
165
],
[
489,
158.5
],
[
500,
123.5
],
[
500,
102.5
],
[
491.5,
91
],
[
476,
86.5
],
[
479,
53.5
],
[
457,
57.5
],
[
456,
46.5
],
[
463,
35.5
],
[
463,
20.5
],
[
454.5,
5
],
[
444.5,
3
],
[
435,
18.5
],
[
429,
39.5
],
[
431,
55.5
],
[
417,
63.5
],
[
415,
72.5
],
[
425,
96.5
],
[
442,
109.5
],
[
446,
128.5
],
[
440.5,
131
],
[
428.5,
126
],
[
405.5,
128
],
[
389,
142.5
],
[
389,
154.5
],
[
406.5,
161
],
[
421,
181.5
],
[
392.5,
181
],
[
381,
190.5
],
[
378,
197.5
],
[
380,
217.5
],
[
368,
229.5
],
[
365,
239.5
],
[
369,
248.5
],
[
386,
262.5
],
[
388,
270.5
],
[
365,
289.5
],
[
358.5,
310
],
[
339.5,
302
],
[
325,
314.5
],
[
323,
342.5
],
[
337,
353.5
],
[
324,
361.5
],
[
314,
389.5
],
[
316.5,
395
],
[
335,
402.5
],
[
346,
423.5
],
[
343,
437.5
],
[
330,
447.5
],
[
334,
462.5
],
[
349,
471.5
],
[
342,
492.5
],
[
345.5,
499
],
[
559,
499.5
],
[
554,
475.5
],
[
543.5,
472
]
],
"group_id": null,
"shape_type": "polygon",
"flags": {}
},
{
"label": "snapdragon",
"points": [
[
272.5,
358
],
[
277.5,
353
],
[
294.5,
360
],
[
306.5,
377
],
[
314,
377.5
],
[
321,
362.5
],
[
333,
353.5
],
[
321,
342.5
],
[
324,
313.5
],
[
339.5,
300
],
[
355.5,
305
],
[
363,
289.5
],
[
373,
280.5
],
[
379,
261.5
],
[
366,
246.5
],
[
364,
235.5
],
[
379,
215.5
],
[
377,
196.5
],
[
381,
188.5
],
[
404,
175.5
],
[
396.5,
168
],
[
358.5,
175
],
[
358,
160.5
],
[
346,
146.5
],
[
344,
136.5
],
[
331.5,
132
],
[
321,
122.5
],
[
322.5,
118
],
[
335.5,
114
],
[
335.5,
108
],
[
324.5,
103
],
[
301.5,
110
],
[
295,
93.5
],
[
283,
83.5
],
[
280.5,
72
],
[
275,
74.5
],
[
274.5,
85
],
[
259.5,
98
],
[
253.5,
98
],
[
244,
92.5
],
[
243,
68.5
],
[
228.5,
51
],
[
225,
51.5
],
[
228.5,
67
],
[
198.5,
64
],
[
189.5,
68
],
[
186,
55.5
],
[
175.5,
42
],
[
167,
44.5
],
[
164.5,
54
],
[
151.5,
51
],
[
133.5,
61
],
[
107.5,
56
],
[
95,
65.5
],
[
84,
84.5
],
[
94,
118.5
],
[
119,
146.5
],
[
110,
202.5
],
[
96,
219.5
],
[
89,
242.5
],
[
93,
255.5
],
[
82,
271.5
],
[
84,
285.5
],
[
92.5,
297
],
[
119,
311.5
],
[
113,
324.5
],
[
117,
343.5
],
[
131.5,
358
],
[
146.5,
362
],
[
165.5,
358
],
[
203.5,
317
],
[
217.5,
324
],
[
241.5,
319
],
[
247,
351.5
],
[
234,
371.5
],
[
234,
379.5
],
[
239,
382.5
],
[
255.5,
361
],
[
272.5,
358
]
],
"group_id": null,
"shape_type": "polygon",
"flags": {}
}
],
"imagePath": "firc_flower_3124.jpg",
"imageData": null,
"imageHeight": 500,
"imageWidth": 666
}本文参与 腾讯云自媒体同步曝光计划，分享自作者个人站点/博客。
原始发表：2025-04-15，如有侵权请联系 cloudcommunity@tencent.com 删除
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