首页下载资源人工智能yolov5实现人群计数

ZIPyolov5实现人群计数

qq_3685284030.58MB需要积分:1

资源文件列表:

yolov5.zip 大约有266个文件
  1. yolov5/
  2. yolov5/.dockerignore 3.61KB
  3. yolov5/.git/
  4. yolov5/.git/branches/
  5. yolov5/.git/config 301B
  6. yolov5/.git/description 73B
  7. yolov5/.git/FETCH_HEAD
  8. yolov5/.git/HEAD 23B
  9. yolov5/.git/hooks/
  10. yolov5/.git/hooks/applypatch-msg.sample 478B
  11. yolov5/.git/hooks/commit-msg.sample 896B
  12. yolov5/.git/hooks/fsmonitor-watchman.sample 4.55KB
  13. yolov5/.git/hooks/post-update.sample 189B
  14. yolov5/.git/hooks/pre-applypatch.sample 424B
  15. yolov5/.git/hooks/pre-commit.sample 1.6KB
  16. yolov5/.git/hooks/pre-merge-commit.sample 416B
  17. yolov5/.git/hooks/pre-push.sample 1.34KB
  18. yolov5/.git/hooks/pre-rebase.sample 4.78KB
  19. yolov5/.git/hooks/pre-receive.sample 544B
  20. yolov5/.git/hooks/prepare-commit-msg.sample 1.46KB
  21. yolov5/.git/hooks/push-to-checkout.sample 2.72KB
  22. yolov5/.git/hooks/update.sample 3.56KB
  23. yolov5/.git/index 13.65KB
  24. yolov5/.git/info/
  25. yolov5/.git/info/exclude 240B
  26. yolov5/.git/logs/
  27. yolov5/.git/logs/HEAD 180B
  28. yolov5/.git/logs/refs/
  29. yolov5/.git/logs/refs/heads/
  30. yolov5/.git/logs/refs/heads/master 180B
  31. yolov5/.git/logs/refs/remotes/
  32. yolov5/.git/logs/refs/remotes/origin/
  33. yolov5/.git/logs/refs/remotes/origin/HEAD 180B
  34. yolov5/.git/logs/refs/remotes/origin/master 146B
  35. yolov5/.git/objects/
  36. yolov5/.git/objects/24/
  37. yolov5/.git/objects/24/ee28010fbf597ec796e6e471429cde21040f90 914B
  38. yolov5/.git/objects/5b/
  39. yolov5/.git/objects/5b/00f52a9c9b57a5c9488f364fdc722d84353712 1.02KB
  40. yolov5/.git/objects/70/
  41. yolov5/.git/objects/70/f86cf95cc04704b747a8e94941e70d5d09f954 546B
  42. yolov5/.git/objects/71/
  43. yolov5/.git/objects/71/81460581ece02ea70b2fe842d2ccf4173eb278 291B
  44. yolov5/.git/objects/78/
  45. yolov5/.git/objects/78/3d877b23a75d2d39dbd639f51a43fe12167363 133B
  46. yolov5/.git/objects/8e/
  47. yolov5/.git/objects/8e/f7f74c9d8b48e6a74c5cb4ce0a6af8a7e8b6d0 11.38KB
  48. yolov5/.git/objects/93/
  49. yolov5/.git/objects/93/33f862dd72920841e90ec0e26f9d0b18d6abfd 151B
  50. yolov5/.git/objects/9f/
  51. yolov5/.git/objects/9f/2f78e636ddbd7944da3ca6db66e8f20ea5f105 2.19KB
  52. yolov5/.git/objects/b3/
  53. yolov5/.git/objects/b3/83deb7e917fef801adcb31756a57382f8d743a 12.33KB
  54. yolov5/.git/objects/bb/
  55. yolov5/.git/objects/bb/5c1f99689e96abce764894c0182093d130fa71 12.46KB
  56. yolov5/.git/objects/c5/
  57. yolov5/.git/objects/c5/47a29a9c9c20ea82fd4a0823d741f7bf1d0fcc 22.84KB
  58. yolov5/.git/objects/cf/
  59. yolov5/.git/objects/cf/3d27b8731362f97e11741768b576845840a355 1.02KB
  60. yolov5/.git/objects/d3/
  61. yolov5/.git/objects/d3/9f824a4f2fdbede6ecb1ee4dde0345262debbf 10.65KB
  62. yolov5/.git/objects/e2/
  63. yolov5/.git/objects/e2/21fbc32a11cbb33a13b4984b1cee6a3d2be79a 150B
  64. yolov5/.git/objects/fd/
  65. yolov5/.git/objects/fd/5b7bad101f26c101b7118fc5281c087574da2b 779B
  66. yolov5/.git/objects/info/
  67. yolov5/.git/objects/pack/
  68. yolov5/.git/objects/pack/pack-3362ae32d143657d388225798105f5f0a60d9ada.idx 465.97KB
  69. yolov5/.git/objects/pack/pack-3362ae32d143657d388225798105f5f0a60d9ada.pack 15.73MB
  70. yolov5/.git/packed-refs 1.23KB
  71. yolov5/.git/refs/
  72. yolov5/.git/refs/heads/
  73. yolov5/.git/refs/heads/master 41B
  74. yolov5/.git/refs/remotes/
  75. yolov5/.git/refs/remotes/origin/
  76. yolov5/.git/refs/remotes/origin/HEAD 32B
  77. yolov5/.git/refs/remotes/origin/master 41B
  78. yolov5/.git/refs/tags/
  79. yolov5/.gitattributes 75B
  80. yolov5/.github/
  81. yolov5/.github/dependabot.yml 649B
  82. yolov5/.github/ISSUE_TEMPLATE/
  83. yolov5/.github/ISSUE_TEMPLATE/bug-report.yml 2.9KB
  84. yolov5/.github/ISSUE_TEMPLATE/config.yml 405B
  85. yolov5/.github/ISSUE_TEMPLATE/feature-request.yml 1.79KB
  86. yolov5/.github/ISSUE_TEMPLATE/question.yml 1.17KB
  87. yolov5/.github/workflows/
  88. yolov5/.github/workflows/ci-testing.yml 6.8KB
  89. yolov5/.github/workflows/cla.yml 1.57KB
  90. yolov5/.github/workflows/codeql-analysis.yml 1.17KB
  91. yolov5/.github/workflows/docker.yml 1.66KB
  92. yolov5/.github/workflows/format.yml 5.34KB
  93. yolov5/.github/workflows/links.yml 2.74KB
  94. yolov5/.github/workflows/merge-main-into-prs.yml 3.02KB
  95. yolov5/.github/workflows/stale.yml 2.31KB
  96. yolov5/.gitignore 3.92KB
  97. yolov5/benchmarks.py 13.79KB
  98. yolov5/CITATION.cff 393B
  99. yolov5/classify/
  100. yolov5/classify/predict.py 11.81KB
  101. yolov5/classify/train.py 16.1KB
  102. yolov5/classify/tutorial.ipynb 93.67KB
  103. yolov5/classify/val.py 8.01KB
  104. yolov5/CONTRIBUTING.md 4.89KB
  105. yolov5/data/
  106. yolov5/data/Argoverse.yaml 2.66KB
  107. yolov5/data/coco.yaml 2.43KB
  108. yolov5/data/coco128-seg.yaml 1.85KB
  109. yolov5/data/coco128.yaml 1.83KB
  110. yolov5/data/GlobalWheat2020.yaml 1.84KB
  111. yolov5/data/hyps/
  112. yolov5/data/hyps/hyp.no-augmentation.yaml 1.61KB
  113. yolov5/data/hyps/hyp.Objects365.yaml 671B
  114. yolov5/data/hyps/hyp.scratch-high.yaml 1.61KB
  115. yolov5/data/hyps/hyp.scratch-low.yaml 1.62KB
  116. yolov5/data/hyps/hyp.scratch-med.yaml 1.62KB
  117. yolov5/data/hyps/hyp.VOC.yaml 1.13KB
  118. yolov5/data/ImageNet.yaml 18.42KB
  119. yolov5/data/ImageNet10.yaml 929B
  120. yolov5/data/ImageNet100.yaml 2.58KB
  121. yolov5/data/ImageNet1000.yaml 18.42KB
  122. yolov5/data/images/
  123. yolov5/data/images/bus.jpg 476.01KB
  124. yolov5/data/images/zidane.jpg 164.99KB
  125. yolov5/data/Objects365.yaml 8.98KB
  126. yolov5/data/scripts/
  127. yolov5/data/scripts/download_weights.sh 641B
  128. yolov5/data/scripts/get_coco.sh 1.53KB
  129. yolov5/data/scripts/get_coco128.sh 619B
  130. yolov5/data/scripts/get_imagenet.sh 1.63KB
  131. yolov5/data/scripts/get_imagenet10.sh 734B
  132. yolov5/data/scripts/get_imagenet100.sh 738B
  133. yolov5/data/scripts/get_imagenet1000.sh 742B
  134. yolov5/data/SKU-110K.yaml 2.28KB
  135. yolov5/data/VisDrone.yaml 2.9KB
  136. yolov5/data/VOC.yaml 3.41KB
  137. yolov5/data/xView.yaml 5.04KB
  138. yolov5/export.py 66.14KB
  139. yolov5/hubconf.py 23.41KB
  140. yolov5/LICENSE 33.71KB
  141. yolov5/models/
  142. yolov5/models/common.py 50.89KB
  143. yolov5/models/experimental.py 5.03KB
  144. yolov5/models/hub/
  145. yolov5/models/hub/anchors.yaml 3.26KB
  146. yolov5/models/hub/yolov3-spp.yaml 1.55KB
  147. yolov5/models/hub/yolov3-tiny.yaml 1.22KB
  148. yolov5/models/hub/yolov3.yaml 1.54KB
  149. yolov5/models/hub/yolov5-bifpn.yaml 1.41KB
  150. yolov5/models/hub/yolov5-fpn.yaml 1.2KB
  151. yolov5/models/hub/yolov5-p2.yaml 1.66KB
  152. yolov5/models/hub/yolov5-p34.yaml 1.21KB
  153. yolov5/models/hub/yolov5-p6.yaml 1.71KB
  154. yolov5/models/hub/yolov5-p7.yaml 2.09KB
  155. yolov5/models/hub/yolov5-panet.yaml 1.39KB
  156. yolov5/models/hub/yolov5l6.yaml 1.79KB
  157. yolov5/models/hub/yolov5m6.yaml 1.79KB
  158. yolov5/models/hub/yolov5n6.yaml 1.79KB
  159. yolov5/models/hub/yolov5s-ghost.yaml 1.46KB
  160. yolov5/models/hub/yolov5s-LeakyReLU.yaml 1.48KB
  161. yolov5/models/hub/yolov5s-transformer.yaml 1.42KB
  162. yolov5/models/hub/yolov5s6.yaml 1.79KB
  163. yolov5/models/hub/yolov5x6.yaml 1.79KB
  164. yolov5/models/segment/
  165. yolov5/models/segment/yolov5l-seg.yaml 1.39KB
  166. yolov5/models/segment/yolov5m-seg.yaml 1.4KB
  167. yolov5/models/segment/yolov5n-seg.yaml 1.4KB
  168. yolov5/models/segment/yolov5s-seg.yaml 1.4KB
  169. yolov5/models/segment/yolov5x-seg.yaml 1.4KB
  170. yolov5/models/tf.py 32.97KB
  171. yolov5/models/yolo.py 20.54KB
  172. yolov5/models/yolov5l.yaml 1.38KB
  173. yolov5/models/yolov5m.yaml 1.39KB
  174. yolov5/models/yolov5n.yaml 1.39KB
  175. yolov5/models/yolov5s.yaml 1.39KB
  176. yolov5/models/yolov5x.yaml 1.39KB
  177. yolov5/models/__init__.py
  178. yolov5/models/__pycache__/
  179. yolov5/models/__pycache__/common.cpython-38.pyc 48.04KB
  180. yolov5/models/__pycache__/experimental.cpython-38.pyc 5.83KB
  181. yolov5/models/__pycache__/yolo.cpython-38.pyc 19.27KB
  182. yolov5/models/__pycache__/__init__.cpython-38.pyc 164B
  183. yolov5/person_count.py 23.52KB
  184. yolov5/pyproject.toml 5.25KB
  185. yolov5/README.md 42.15KB
  186. yolov5/README.zh-CN.md 42.25KB
  187. yolov5/requirements.txt 1.56KB
  188. yolov5/runs/
  189. yolov5/segment/
  190. yolov5/segment/predict.py 15.91KB
  191. yolov5/segment/train.py 34.35KB
  192. yolov5/segment/tutorial.ipynb 40.08KB
  193. yolov5/segment/val.py 23.8KB
  194. yolov5/test.jpg 427.76KB
  195. yolov5/train.py 46.03KB
  196. yolov5/tutorial.ipynb 40.45KB
  197. yolov5/utils/
  198. yolov5/utils/activations.py 4.89KB
  199. yolov5/utils/augmentations.py 18.51KB
  200. yolov5/utils/autoanchor.py 7.75KB
  201. yolov5/utils/autobatch.py 2.97KB
  202. yolov5/utils/aws/
  203. yolov5/utils/aws/mime.sh 780B
  204. yolov5/utils/aws/resume.py 1.21KB
  205. yolov5/utils/aws/userdata.sh 1.22KB
  206. yolov5/utils/aws/__init__.py
  207. yolov5/utils/callbacks.py 2.65KB
  208. yolov5/utils/dataloaders.py 59.07KB
  209. yolov5/utils/docker/
  210. yolov5/utils/docker/Dockerfile 2.5KB
  211. yolov5/utils/docker/Dockerfile-arm64 1.53KB
  212. yolov5/utils/docker/Dockerfile-cpu 1.78KB
  213. yolov5/utils/downloads.py 5.11KB
  214. yolov5/utils/flask_rest_api/
  215. yolov5/utils/flask_rest_api/example_request.py 365B
  216. yolov5/utils/flask_rest_api/README.md 1.68KB
  217. yolov5/utils/flask_rest_api/restapi.py 1.54KB
  218. yolov5/utils/general.py 50.24KB
  219. yolov5/utils/google_app_engine/
  220. yolov5/utils/google_app_engine/additional_requirements.txt 264B
  221. yolov5/utils/google_app_engine/app.yaml 219B
  222. yolov5/utils/google_app_engine/Dockerfile 821B
  223. yolov5/utils/loggers/
  224. yolov5/utils/loggers/clearml/
  225. yolov5/utils/loggers/clearml/clearml_utils.py 9.47KB
  226. yolov5/utils/loggers/clearml/hpo.py 5.17KB
  227. yolov5/utils/loggers/clearml/README.md 10.58KB
  228. yolov5/utils/loggers/clearml/__init__.py
  229. yolov5/utils/loggers/comet/
  230. yolov5/utils/loggers/comet/comet_utils.py 4.71KB
  231. yolov5/utils/loggers/comet/hpo.py 6.77KB
  232. yolov5/utils/loggers/comet/optimizer_config.json 2.37KB
  233. yolov5/utils/loggers/comet/README.md 10.56KB
  234. yolov5/utils/loggers/comet/__init__.py 21.09KB
  235. yolov5/utils/loggers/wandb/
  236. yolov5/utils/loggers/wandb/wandb_utils.py 7.95KB
  237. yolov5/utils/loggers/wandb/__init__.py
  238. yolov5/utils/loggers/__init__.py 19.78KB
  239. yolov5/utils/loss.py 11.11KB
  240. yolov5/utils/metrics.py 15.13KB
  241. yolov5/utils/plots.py 20.21KB
  242. yolov5/utils/segment/
  243. yolov5/utils/segment/augmentations.py 3.68KB
  244. yolov5/utils/segment/dataloaders.py 13.38KB
  245. yolov5/utils/segment/general.py 5.8KB
  246. yolov5/utils/segment/loss.py 9KB
  247. yolov5/utils/segment/metrics.py 5.88KB
  248. yolov5/utils/segment/plots.py 6.53KB
  249. yolov5/utils/segment/__init__.py
  250. yolov5/utils/torch_utils.py 21.15KB
  251. yolov5/utils/triton.py 3.7KB
  252. yolov5/utils/__init__.py 3.17KB
  253. yolov5/utils/__pycache__/
  254. yolov5/utils/__pycache__/augmentations.cpython-38.pyc 16.5KB
  255. yolov5/utils/__pycache__/autoanchor.cpython-38.pyc 6.82KB
  256. yolov5/utils/__pycache__/dataloaders.cpython-38.pyc 49.1KB
  257. yolov5/utils/__pycache__/downloads.cpython-38.pyc 4.76KB
  258. yolov5/utils/__pycache__/general.cpython-38.pyc 45.55KB
  259. yolov5/utils/__pycache__/metrics.cpython-38.pyc 12.28KB
  260. yolov5/utils/__pycache__/plots.cpython-38.pyc 19.54KB
  261. yolov5/utils/__pycache__/torch_utils.cpython-38.pyc 19.65KB
  262. yolov5/utils/__pycache__/__init__.cpython-38.pyc 3.61KB
  263. yolov5/val.py 29.71KB
  264. yolov5/yolov5s.pt 14.12MB
  265. yolov5/__pycache__/
  266. yolov5/__pycache__/export.cpython-38.pyc 56.73KB

资源介绍:

本项目是一个使用 YOLOv5 模型实现的人群计数 Python 应用。YOLOv5 是一个流行的目标检测模型，以其速度快和准确性高而闻名。通过这个项目，你可以快速部署一个能够识别图像中人数的系统。 功能特点： 高精度人群计数：利用 YOLOv5 模型的高效目标检测能力，实现对人群的精确计数。 实时图像处理：支持从摄像头或视频文件中实时读取图像，并进行人群计数。 易于集成：代码结构清晰，易于与其他系统或应用集成。 跨平台支持：兼容主流操作系统，包括 Windows、Linux 和 macOS。 技术栈： Python：编程语言。 YOLOv5：目标检测模型。 OpenCV：用于图像处理和显示。

[涓枃](https://docs.ultralytics.com/zh) | [頃滉淡鞏碷(https://docs.ultralytics.com/ko) | [鏃ユ湰瑾瀅(https://docs.ultralytics.com/ja) | [袪褍褋褋泻懈泄](https://docs.ultralytics.com/ru) | [Deutsch](https://docs.ultralytics.com/de) | [Fran莽ais](https://docs.ultralytics.com/fr) | [Espa帽ol](https://docs.ultralytics.com/es) | [Portugu锚s](https://docs.ultralytics.com/pt) | [T眉rk莽e](https://docs.ultralytics.com/tr) | [Ti岷縩g Vi峄噒](https://docs.ultralytics.com/vi) | [丕賱毓乇亘賷丞](https://docs.ultralytics.com/ar)
YOLOv5 CI YOLOv5 Citation Docker Pulls Discord Ultralytics Forums Ultralytics Reddit
Run on Gradient Open In Colab Open In Kaggle

YOLOv5 馃殌 is the world's most loved vision AI, representing Ultralytics open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development. We hope that the resources here will help you get the most out of YOLOv5. Please browse the YOLOv5 Docs for details, raise an issue on GitHub for support, and join our Discord community for questions and discussions! To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license).
Ultralytics GitHub Ultralytics LinkedIn Ultralytics Twitter Ultralytics YouTube Ultralytics TikTok Ultralytics BiliBili Ultralytics Discord

##
YOLOv8 馃殌 NEW
We are thrilled to announce the launch of Ultralytics YOLOv8 馃殌, our NEW cutting-edge, state-of-the-art (SOTA) model released at **[https://github.com/ultralytics/ultralytics](https://github.com/ultralytics/ultralytics)**. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection, image segmentation and image classification tasks. See the [YOLOv8 Docs](https://docs.ultralytics.com/) for details and get started with: [![PyPI version](https://badge.fury.io/py/ultralytics.svg)](https://badge.fury.io/py/ultralytics) [![Downloads](https://static.pepy.tech/badge/ultralytics)](https://pepy.tech/project/ultralytics) ```bash pip install ultralytics ```
##
Documentation
See the [YOLOv5 Docs](https://docs.ultralytics.com/yolov5/) for full documentation on training, testing and deployment. See below for quickstart examples.
Install Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.8.0**](https://www.python.org/) environment, including [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). ```bash git clone https://github.com/ultralytics/yolov5 # clone cd yolov5 pip install -r requirements.txt # install ```
Inference YOLOv5 [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading/) inference. [Models](https://github.com/ultralytics/yolov5/tree/master/models) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases). ```python import torch # Model model = torch.hub.load("ultralytics/yolov5", "yolov5s") # or yolov5n - yolov5x6, custom # Images img = "https://ultralytics.com/images/zidane.jpg" # or file, Path, PIL, OpenCV, numpy, list # Inference results = model(img) # Results results.print() # or .show(), .save(), .crop(), .pandas(), etc. ```
Inference with detect.py `detect.py` runs inference on a variety of sources, downloading [models](https://github.com/ultralytics/yolov5/tree/master/models) automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases) and saving results to `runs/detect`. ```bash python detect.py --weights yolov5s.pt --source 0 # webcam img.jpg # image vid.mp4 # video scre
100+评论
captcha

    相关资源

    1. javaweb项目鲜花商城管理系统spring+springMVC+mybatis+mysql-java课程设计毕业设计

      csm2017#后端ZIP64.53MB4月前
      资源摘要:采用了Spring、Spring MVC、MyBatis和MySQL**等热门开发框架，专为在校大学生的Java课程设计和毕业设计提供学习参考和实践指导。通过本项目，您将能够学习到如何使用Spring框架搭建高效的后端服务，如何运用MyBatis进行数据持久化操作，以及如何通过Spring MVC实现前后端的交互。

    2. STM32F407 HAL库：双DAC的信号发生器+双ADC采集

      2401_83192228#硬件开发ZIP16.75MB4月前
      资源摘要:源代码

    3. javaweb项目校园社团管理系统spring+springMVC+mybatis+mysql-java课程设计毕业设计

      csm2017#后端ZIP87.54MB4月前
      资源摘要:本项目是一个校园社团管理系统，采用Spring、SpringMVC、MyBatis和MySQL技术栈开发，旨在为在校大学生提供高效的社团管理解决方案。系统包括社团信息管理、学生信息管理、通知信息管理、活动信息管理等功能模块，方便社团组织者和成员进行日常管理和信息交流。该源码适合用于Java课程设计和毕业设计，帮助学生深入理解JavaWeb开发的核心技术及应用。无论是Java初学者还是有一定基础的技术爱好者，都可以通过本项目获取宝贵的学习资料和实践经验。通过分析和改进该系统，用户能够提升自己的编程能力和项目管理技能。

    4. 10篇代码生成的论文，包括代码评估、代码搜索、代码生成、survey、代码或bug分类

      sinat_37574187#人工智能ZIP7.68MB4月前
      资源摘要:题目类型分区摘要精读链接Comparing large language models and humanprogrammers for generating programming code代码评估arxiv评估七种LLMs在生成编程代码方面的性能，探讨不同提示策略对LLMs编码性能的影响，直接比较LLMs与人类程序员的编程能力，评估LLMs在不同编程语言之间生成和翻译代码的能力，以及考察LLMs的计算效率和从过去错误中学习的能力。A Comparison of the Effectiveness of ChatGPT andCo-Pilot for Generating Quality Python Code代码评估会议包括评估ChatGPT和Copilot在解决LeetCode编程问题上的有效性，探讨ChatGPT在接收到反馈后纠正代码的能力，以及其在提高代码质量和性能方面的潜力。Program Code Generation with Generative AIs代码评估MDPI水刊-Algorithms非SCI比较了人类生成的代码

    5. 基于大数据hadoop图书分析系统框架html + css + jquery + python +Django + hadoo

      Strategic__#后端ZIP8.46MB4月前
      资源摘要:基于大数据hadoop图书分析系统框架html + css + jquery + python +Django + hadoop + hive + hdfs + MySQL + orm用户类型管理员admin123456普通用户qqq123456模块介绍管理员登录注册系统首页 可视化统计子模块不同类别价格子模块不同类型出版社图书详细信息图书预览图书推荐个人信息子模块密码修改子模块图书大屏系统设置子模块退出系统普通用户登录注册系统首页 图书详细信息图书预览图书推荐个人信息子模块密码修改系统设置子模块退出系统数据库设计booksdb

    6. 关于组织2025年校级大学生创新训练计划项目立项的通知.zip

      2401_87401643#行业研究ZIP106.31KB4月前
      资源摘要:关于组织2025年校级大学生创新训练计划项目立项的通知.zip

    7. Springboot个性化图书推荐系统

      weixin_46115961#后端ZIP9.12MB4月前
      资源摘要:Springboot个性化图书推荐系统采用Springboot，vue，mysql等技术，主要用户分为管理员和学生，实现功能包括管理员:首页、个人中心、学生管理、图书分类管理、图书信息管理、图书预约管理、退换图书管理、管理员管 理、留言板管理、系统管理，学生:首页、个人中心、图书预约管理、退换图书管理、我的 收藏管理，前台首页;首页、图书信息、好书推荐、留言反馈、个人中心、后台管理等功能。

    8. 基于JavaSwing的简单计算器

      qq_50801874#后端ZIP8.03KB4月前
      资源摘要:基于JavaSwing的简单计算器
    站长QQ:九六九五七三七