/ssd/train/0144827586207-97_84-471&395_653&483-643&475_477&452_479&403_645&426-0_0_6_33_24_24_6-56-36.jpg /ssd/annotation/train/0144827586207-97_84-471&395_653&483-643&475_477&452_479&403_645&426-0_0_6_33_24_24_6-56-36.xml
/ssd/train/0301724137931-100_81-132&467_392&598-384&579_146&537_148&474_386&516-0_0_9_27_16_33_25-99-24.jpg /ssd/annotation/train/0301724137931-100_81-132&467_392&598-384&579_146&537_148&474_386&516-0_0_9_27_16_33_25-99-24.xml
/ssd/train/0427681992338-120_55-195&478_398&682-393&673_211&565_205&483_388&591-0_0_2_8_29_31_25-136-81.jpg /ssd/annotation/train/0427681992338-120_55-195&478_398&682-393&673_211&565_205&483_388&591-0_0_2_8_29_31_25-136-81.xml
/ssd/train/00497844827586-90_85-323&437_462&487-456&484_332&482_330&451_454&453-0_0_7_31_26_30_2-78-19.jpg /ssd/annotation/train/00497844827586-90_85-323&437_462&487-456&484_332&482_330&451_454&453-0_0_7_31_26_30_2-78-19.xml
/ssd/train/0464511494253-89_91-265&334_646&468-641&437_276&449_275&355_641&343-0_0_2_26_32_33_18-81-81.jpg /ssd/annotation/train/0464511494253-89_91-265&334_646&468-641&437_276&449_275&355_641&343-0_0_2_26_32_33_18-81-81.xml
/ssd/train/0162871168583-90_90-351&462_584&527-580&520_357&523_357&465_579&462-0_0_22_24_29_30_10-101-29.jpg /ssd/annotation/train/0162871168583-90_90-351&462_584&527-580&520_357&523_357&465_579&462-0_0_22_24_29_30_10-101-29.xml
/ssd/train/0258500957855-89_89-223&467_512&572-503&551_252&559_249&482_500&474-10_0_5_31_27_19_29-158-83.jpg /ssd/annotation/train/0258500957855-89_89-223&467_512&572-503&551_252&559_249&482_500&474-10_0_5_31_27_19_29-158-83.xml
/ssd/train/0171527777778-90_89-203&539_461&607-456&601_209&599_209&543_455&544-0_0_30_16_29_27_30-162-92.jpg /ssd/annotation/train/0171527777778-90_89-203&539_461&607-456&601_209&599_209&543_455&544-0_0_30_16_29_27_30-162-92.xml
/ssd/train/0267780172414-100_70-276&502_503&643-495&619_293&582_282&514_485&551-0_0_7_31_29_30_10-43-29.jpg /ssd/annotation/train/0267780172414-100_70-276&502_503&643-495&619_293&582_282&514_485&551-0_0_7_31_29_30_10-43-29.xml
/ssd/train/00782567049809-90_90-354&386_533&454-516&446_365&445_366&403_517&404-0_0_23_7_29_31_29-26-12.jpg /ssd/annotation/train/00782567049809-90_90-354&386_533&454-516&446_365&445_366&403_517&404-0_0_23_7_29_31_29-26-12.xml
/ssd/train/00609674329502-90_86-407&365_553&413-545&409_413&409_411&371_543&372-10_4_30_32_2_14_29-128-18.jpg /ssd/annotation/train/00609674329502-90_86-407&365_553&413-545&409_413&409_411&371_543&372-10_4_30_32_2_14_29-128-18.xml
/ssd/train/023275862069-93_84-176&335_435&431-428&420_191&406_188&339_425&353-0_0_25_30_33_11_25-87-42.jpg /ssd/annotation/train/023275862069-93_84-176&335_435&431-428&420_191&406_188&339_425&353-0_0_25_30_33_11_25-87-42.xml
/ssd/train/0114559386973-90_92-290&317_489&381-482&365_299&369_300&320_483&317-0_0_7_6_27_32_27-148-59.jpg /ssd/annotation/train/0114559386973-90_92-290&317_489&381-482&365_299&369_300&320_483&317-0_0_7_6_27_32_27-148-59.xml
/ssd/train/0451388888889-88_87-225&464_602&571-604&552_235&570_227&489_596&470-0_2_17_30_24_32_33-93-231.jpg /ssd/annotation/train/0451388888889-88_87-225&464_602&571-604&552_235&570_227&489_596&470-0_2_17_30_24_32_33-93-231.xml
/ssd/train/0188362068966-93_83-220&440_447&536-433&521_230&509_226&445_429&457-0_1_1_2_24_27_27-139-20.jpg /ssd/annotation/train/0188362068966-93_83-220&440_447&536-433&521_230&509_226&445_429&457-0_1_1_2_24_27_27-139-20.xml
/ssd/train/0178975095786-89_97-279&518_497&611-484&595_288&600_295&531_490&526-0_0_3_2_27_29_29-57-33.jpg /ssd/annotation/train/0178975095786-89_97-279&518_497&611-484&595_288&600_295&531_490&526-0_0_3_2_27_29_29-57-33.xml
/ssd/train/0155675287357-92_85-123&486_328&554-326&552_131&543_129&486_324&495-0_0_17_1_28_28_28-131-40.jpg /ssd/annotation/train/0155675287357-92_85-123&486_328&554-326&552_131&543_129&486_324&495-0_0_17_1_28_28_28-131-40.xml
/ssd/train/037341954023-82_105-260&400_549&524-534&478_266&517_275&443_542&404-0_0_19_29_28_25_32-103-53.jpg /ssd/annotation/train/037341954023-82_105-260&400_549&524-534&478_266&517_275&443_542&404-0_0_19_29_28_25_32-103-53.xml
/ssd/train/00799090038314-92_87-220&370_384&440-373&426_231&419_231&379_372&386-0_0_32_32_8_31_29-117-19.jpg /ssd/annotation/train/00799090038314-92_87-220&370_384&440-373&426_231&419_231&379_372&386-0_0_32_32_8_31_29-117-19.xml
/ssd/train/0215301724138-89_94-348&465_585&560-577&545_357&552_360&478_579&471-0_0_14_3_26_31_29-177-47.jpg /ssd/annotation/train/0215301724138-89_94-348&465_585&560-577&545_357&552_360&478_579&471-0_0_14_3_26_31_29-177-47.xml
/ssd/train/0150694444445-89_83-219&455_437&536-434&518_239&522_231&464_426&460-0_0_9_25_24_31_2-95-84.jpg /ssd/annotation/train/0150694444445-89_83-219&455_437&536-434&518_239&522_231&464_426&460-0_0_9_25_24_31_2-95-84.xml
/ssd/train/0321012931034-90_101-189&494_526&597-503&584_188&586_204&507_519&505-0_0_23_7_26_28_30-107-73.jpg /ssd/annotation/train/0321012931034-90_101-189&494_526&597-503&584_188&586_204&507_519&505-0_0_23_7_26_28_30-107-73.xml
/ssd/train/00820641762452-90_93-335&459_501&519-492&506_344&508_346&464_493&462-0_0_3_11_31_31_33-143-23.jpg /ssd/annotation/train/00820641762452-90_93-335&459_501&519-492&506_344&508_346&464_493&462-0_0_3_11_31_31_33-143-23.xml
/ssd/train/0140972222222-91_73-83&363_310&429-304&426_115&420_101&368_290&373-0_0_16_29_25_30_21-54-30.jpg /ssd/annotation/train/0140972222222-91_73-83&363_310&429-304&426_115&420_101&368_290&373-0_0_16_29_25_30_21-54-30.xml
/ssd/train/0215014367816-91_83-179&468_455&572-438&553_197&544_192&480_434&488-0_0_23_20_32_28_33-81-42.jpg /ssd/annotation/train/0215014367816-91_83-179&468_455&572-438&553_197&544_192&480_434&488-0_0_23_20_32_28_33-81-42.xml
/ssd/train/0233836206897-90_91-257&480_556&564-544&553_265&554_266&486_544&484-0_0_23_26_33_31_24-58-58.jpg /ssd/annotation/train/0233836206897-90_91-257&480_556&564-544&553_265&554_266&486_544&484-0_0_23_26_33_31_24-58-58.xml
/ssd/train/0129166666667-90_82-143&604_329&678-328&665_150&667_142&611_319&609-0_0_7_19_25_30_24-119-51.jpg /ssd/annotation/train/0129166666667-90_82-143&604_329&678-328&665_150&667_142&611_319&609-0_0_7_19_25_30_24-119-51.xml
/ssd/train/0289511494253-90_87-171&437_506&541-496&526_189&527_186&449_494&449-0_0_0_33_5_33_29-53-22.jpg /ssd/annotation/train/0289511494253-90_87-171&437_506&541-496&526_189&527_186&449_494&449-0_0_0_33_5_33_29-53-22.xml
/ssd/train/0381681034483-90_91-193&396_536&504-523&490_201&494_202&399_523&395-0_0_32_32_28_13_25-111-129.jpg /ssd/annotation/train/0381681034483-90_91-193&396_536&504-523&490_201&494_202&399_523&395-0_0_32_32_28_13_25-111-129.xml
/ssd/train/0250862068966-105_62-191&455_406&578-398&568_217&518_204&460_385&509-0_0_13_27_26_32_8-114-31.jpg /ssd/annotation/train/0250862068966-105_62-191&455_406&578-398&568_217&518_204&460_385&509-0_0_13_27_26_32_8-114-31.xml
/ssd/train/0111973180076-89_94-255&394_455&459-437&450_272&453_275&400_439&397-0_0_13_22_32_24_30-111-25.jpg /ssd/annotation/train/0111973180076-89_94-255&394_455&459-437&450_272&453_275&400_439&397-0_0_13_22_32_24_30-111-25.xml
/ssd/train/0111745689655-90_91-342&457_543&521-526&506_345&504_347&455_528&458-0_0_33_20_31_30_26-131-37.jpg /ssd/annotation/train/0111745689655-90_91-342&457_543&521-526&506_345&504_347&455_528&458-0_0_33_20_31_30_26-131-37.xml
/ssd/train/0137859195402-89_87-199&361_430&426-411&421_212&425_209&372_408&368-0_0_9_29_3_33_30-92-38.jpg /ssd/annotation/train/0137859195402-89_87-199&361_430&426-411&421_212&425_209&372_408&368-0_0_9_29_3_33_30-92-38.xml
/ssd/train/0082974137931-90_86-279&467_450&528-444&519_292&517_290&474_442&476-0_0_33_25_14_26_33-191-20.jpg /ssd/annotation/train/0082974137931-90_86-279&467_450&528-444&519_292&517_290&474_442&476-0_0_33_25_14_26_33-191-20.xml
/ssd/train/0182614942529-93_86-214&496_483&567-474&565_228&552_228&503_474&516-0_0_16_29_32_27_27-73-14.jpg /ssd/annotation/train/0182614942529-93_86-214&496_483&567-474&565_228&552_228&503_474&516-0_0_16_29_32_27_27-73-14.xml
/ssd/train/0197030651341-90_87-226&426_492&514-474&502_2
没有合适的资源?快使用搜索试试~ 我知道了~
温馨提示
车牌识别毕设项目-基于python+opencv+ssd+resnet算法的国内车牌检测识别系统源码+使用教程+模型 [项目介绍] demo使用 将测试图片放入sample_images/ 运行demo.py python demo.py 运行结果图片将保存在results/中 准确率测试 将测试图片放入test_images/中,或软链接测试集路径 ln -sf $your_own_path/* test_images/ 运行accuracy_test.py python accuracy_test.py 模型评价 从重采样后的CCPD数据集中随机采样500张作为测试机,车牌识别准确率为94.6%
资源推荐
资源详情
资源评论






























收起资源包目录





































































































共 1168 条
- 1
- 2
- 3
- 4
- 5
- 6
- 12
资源评论


.whl
- 粉丝: 4185
上传资源 快速赚钱
我的内容管理 展开
我的资源 快来上传第一个资源
我的收益
登录查看自己的收益我的积分 登录查看自己的积分
我的C币 登录后查看C币余额
我的收藏
我的下载
下载帮助


最新资源
- 乌鲁木齐高新区新市区软件与信息服务产业基地规划.doc
- 佳木斯港隆东方城项目管理人员现状分析及对策研究.doc
- (源码)基于Arduino的项目模板.zip
- LBM格子波尔兹曼模型在固体融化及固液相变中的应用研究 · LBM 最新版
- 2023年全国计算机二级MSOffice选择题题库大全.doc
- 商机快速匹配买家委托采购大买家采购的运用阿里巴巴国际网站操作手册.doc
- 关于计算机毕业实习报告.docx
- 会计服务与互联网+如何亲密接触【会计实务操作教程】.pptx
- 软件项目管理-立项管理.ppt
- 主题活动:青花瓷(目标及网络图).doc
- GB14887-2011-道路交通信号灯.doc
- 发挥一方主体责任-搞好工程项目管理.doc
- 计算机个人学习心得五篇范文.docx
- Maxwell磁芯仿真技术:原理、方法及其在电机、变压器和电感器中的应用
- 苹果MFi配件iOS软件的两种方案.doc
- (源码)基于LoRa通信技术的电力计量系统.zip
资源上传下载、课程学习等过程中有任何疑问或建议,欢迎提出宝贵意见哦~我们会及时处理!
点击此处反馈



安全验证
文档复制为VIP权益,开通VIP直接复制
