首页下载资源后端yolo数据集制作与简单模型训练

ZIPyolo数据集制作与简单模型训练

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资源文件列表:

plus.zip 大约有1237个文件
  1. plus/
  2. plus/1.py 266B
  3. plus/converted_images/
  4. plus/datasets/
  5. plus/datasets/before/
  6. plus/datasets/before/1.jpg 61.02KB
  7. plus/datasets/before/1.json 83.78KB
  8. plus/datasets/before/10.jpg 52.81KB
  9. plus/datasets/before/10.json 71.98KB
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  11. plus/datasets/before/11.json 75.17KB
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  14. plus/datasets/before/13.jpg 52.25KB
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  17. plus/datasets/before/14.json 60.27KB
  18. plus/datasets/before/15.jpg 48.75KB
  19. plus/datasets/before/15.json 67.99KB
  20. plus/datasets/before/16.jpg 48.74KB
  21. plus/datasets/before/16.json 69.65KB
  22. plus/datasets/before/17.jpg 21.5KB
  23. plus/datasets/before/17.json 31.57KB
  24. plus/datasets/before/18.jpg 68.31KB
  25. plus/datasets/before/18.json 94.34KB
  26. plus/datasets/before/19.jpg 30.45KB
  27. plus/datasets/before/19.json 42.68KB
  28. plus/datasets/before/2.jpg 44.05KB
  29. plus/datasets/before/2.json 60.31KB
  30. plus/datasets/before/20.jpg 30.2KB
  31. plus/datasets/before/20.json 42.92KB
  32. plus/datasets/before/3.jpg 611.3KB
  33. plus/datasets/before/3.json 817.86KB
  34. plus/datasets/before/4.jpg 118.91KB
  35. plus/datasets/before/4.json 160.65KB
  36. plus/datasets/before/5.jpg 611.3KB
  37. plus/datasets/before/5.json 817.72KB
  38. plus/datasets/before/6.jpg 72.57KB
  39. plus/datasets/before/6.json 99.31KB
  40. plus/datasets/before/7.jpg 112.83KB
  41. plus/datasets/before/7.json 152.45KB
  42. plus/datasets/before/8.jpg 69.92KB
  43. plus/datasets/before/8.json 95.29KB
  44. plus/datasets/before/9.jpg 91.43KB
  45. plus/datasets/before/9.json 124.36KB
  46. plus/datasets/image1/
  47. plus/datasets/image1/1.jpg 61.02KB
  48. plus/datasets/image1/10.jpg 52.81KB
  49. plus/datasets/image1/2.jpg 44.05KB
  50. plus/datasets/image1/3.jpg 611.21KB
  51. plus/datasets/image1/4.jpg 118.91KB
  52. plus/datasets/image1/7.jpg 112.83KB
  53. plus/datasets/image1/8.jpg 69.92KB
  54. plus/datasets/image1/9.jpg 91.43KB
  55. plus/datasets/image2/
  56. plus/datasets/image2/11.jpg 54.24KB
  57. plus/datasets/image2/12.jpg 45.39KB
  58. plus/datasets/image2/13.jpg 52.25KB
  59. plus/datasets/image2/14.jpg 42.64KB
  60. plus/datasets/image2/15.jpg 48.75KB
  61. plus/datasets/image2/16.jpg 48.74KB
  62. plus/datasets/image2/17.jpg 21.5KB
  63. plus/datasets/image2/18.jpg 68.31KB
  64. plus/datasets/image2/19.jpg 30.45KB
  65. plus/datasets/image2/20.jpg 30.2KB
  66. plus/datasets/JPEGImages/
  67. plus/datasets/JPEGImages/1.jpg 61.02KB
  68. plus/datasets/JPEGImages/10.jpg 52.81KB
  69. plus/datasets/JPEGImages/11.jpg 54.24KB
  70. plus/datasets/JPEGImages/12.jpg 45.39KB
  71. plus/datasets/JPEGImages/13.jpg 52.25KB
  72. plus/datasets/JPEGImages/14.jpg 42.64KB
  73. plus/datasets/JPEGImages/15.jpg 48.75KB
  74. plus/datasets/JPEGImages/16.jpg 48.74KB
  75. plus/datasets/JPEGImages/17.jpg 21.5KB
  76. plus/datasets/JPEGImages/18.jpg 68.31KB
  77. plus/datasets/JPEGImages/19.jpg 30.45KB
  78. plus/datasets/JPEGImages/2.jpg 44.05KB
  79. plus/datasets/JPEGImages/20.jpg 30.2KB
  80. plus/datasets/JPEGImages/3.jpg 611.21KB
  81. plus/datasets/JPEGImages/4.jpg 118.91KB
  82. plus/datasets/JPEGImages/5.jpg 611.3KB
  83. plus/datasets/JPEGImages/6.jpg 72.57KB
  84. plus/datasets/JPEGImages/7.jpg 112.83KB
  85. plus/datasets/JPEGImages/8.jpg 69.92KB
  86. plus/datasets/JPEGImages/9.jpg 91.43KB
  87. plus/datasets/labels/
  88. plus/datasets/labels/1.txt 53B
  89. plus/datasets/labels/10.txt 79B
  90. plus/datasets/labels/11.txt 53B
  91. plus/datasets/labels/12.txt 27B
  92. plus/datasets/labels/13.txt 39B
  93. plus/datasets/labels/14.txt 25B
  94. plus/datasets/labels/15.txt 51B
  95. plus/datasets/labels/16.txt 52B
  96. plus/datasets/labels/17.txt 53B
  97. plus/datasets/labels/18.txt 55B
  98. plus/datasets/labels/19.txt 67B
  99. plus/datasets/labels/2.txt 55B
  100. plus/datasets/labels/20.txt 53B
  101. plus/datasets/labels/3.txt 64B
  102. plus/datasets/labels/4.txt 55B
  103. plus/datasets/labels/5.txt 82B
  104. plus/datasets/labels/6.txt 63B
  105. plus/datasets/labels/7.txt 64B
  106. plus/datasets/labels/8.txt 55B
  107. plus/datasets/labels/9.txt 61B
  108. plus/datasets/labels1/
  109. plus/datasets/labels1/1.txt 53B
  110. plus/datasets/labels1/10.txt 79B
  111. plus/datasets/labels1/2.txt 51B
  112. plus/datasets/labels1/3.txt 84B
  113. plus/datasets/labels1/4.txt 57B
  114. plus/datasets/labels1/7.txt 81B
  115. plus/datasets/labels1/8.txt 56B
  116. plus/datasets/labels1/9.txt 63B
  117. plus/datasets/labels2/
  118. plus/datasets/labels2/11.txt 53B
  119. plus/datasets/labels2/12.txt 27B
  120. plus/datasets/labels2/13.txt 39B
  121. plus/datasets/labels2/14.txt 25B
  122. plus/datasets/labels2/15.txt 51B
  123. plus/datasets/labels2/16.txt 52B
  124. plus/datasets/labels2/17.txt 53B
  125. plus/datasets/labels2/18.txt 55B
  126. plus/datasets/labels2/19.txt 67B
  127. plus/datasets/labels2/20.txt 53B
  128. plus/datasets/mask/
  129. plus/datasets/mask/1.png 4.03KB
  130. plus/datasets/mask/10.png 4.66KB
  131. plus/datasets/mask/11.png 4.92KB
  132. plus/datasets/mask/12.png 3.88KB
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  134. plus/datasets/mask/14.png 3.48KB
  135. plus/datasets/mask/15.png 3.48KB
  136. plus/datasets/mask/16.png 4.19KB
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  138. plus/datasets/mask/18.png 6.69KB
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  140. plus/datasets/mask/2.png 4.29KB
  141. plus/datasets/mask/20.png 4KB
  142. plus/datasets/mask/3.png 21.23KB
  143. plus/datasets/mask/4.png 7.75KB
  144. plus/datasets/mask/5.png 20.72KB
  145. plus/datasets/mask/6.png 7.37KB
  146. plus/datasets/mask/7.png 7.7KB
  147. plus/datasets/mask/8.png 7.41KB
  148. plus/datasets/mask/9.png 8.12KB
  149. plus/datasets/SegmentationClass/
  150. plus/datasets/SegmentationClass/1.png 4.03KB
  151. plus/datasets/SegmentationClass/10.png 4.66KB
  152. plus/datasets/SegmentationClass/11.png 4.92KB
  153. plus/datasets/SegmentationClass/12.png 3.88KB
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  155. plus/datasets/SegmentationClass/14.png 3.48KB
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  157. plus/datasets/SegmentationClass/16.png 4.19KB
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  161. plus/datasets/SegmentationClass/2.png 4.29KB
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  163. plus/datasets/SegmentationClass/3.png 21.23KB
  164. plus/datasets/SegmentationClass/4.png 7.75KB
  165. plus/datasets/SegmentationClass/5.png 20.72KB
  166. plus/datasets/SegmentationClass/6.png 7.37KB
  167. plus/datasets/SegmentationClass/7.png 7.7KB
  168. plus/datasets/SegmentationClass/8.png 7.41KB
  169. plus/datasets/SegmentationClass/9.png 8.12KB
  170. plus/datasets/spilt_data/
  171. plus/datasets/spilt_data/test/
  172. plus/datasets/spilt_data/test/images/
  173. plus/datasets/spilt_data/test/images/15.jpg 48.75KB
  174. plus/datasets/spilt_data/test/images/17.jpg 21.5KB
  175. plus/datasets/spilt_data/test/labels/
  176. plus/datasets/spilt_data/test/labels/15.txt 51B
  177. plus/datasets/spilt_data/test/labels/17.txt 53B
  178. plus/datasets/spilt_data/train/
  179. plus/datasets/spilt_data/train/images/
  180. plus/datasets/spilt_data/train/images/1.jpg 61.02KB
  181. plus/datasets/spilt_data/train/images/10.jpg 52.81KB
  182. plus/datasets/spilt_data/train/images/11.jpg 54.24KB
  183. plus/datasets/spilt_data/train/images/12.jpg 45.39KB
  184. plus/datasets/spilt_data/train/images/13.jpg 52.25KB
  185. plus/datasets/spilt_data/train/images/14.jpg 42.64KB
  186. plus/datasets/spilt_data/train/images/16.jpg 48.74KB
  187. plus/datasets/spilt_data/train/images/18.jpg 68.31KB
  188. plus/datasets/spilt_data/train/images/19.jpg 30.45KB
  189. plus/datasets/spilt_data/train/images/2.jpg 44.05KB
  190. plus/datasets/spilt_data/train/images/3.jpg 611.21KB
  191. plus/datasets/spilt_data/train/images/4.jpg 118.91KB
  192. plus/datasets/spilt_data/train/images/6.jpg 72.57KB
  193. plus/datasets/spilt_data/train/images/7.jpg 112.83KB
  194. plus/datasets/spilt_data/train/images/8.jpg 69.92KB
  195. plus/datasets/spilt_data/train/images/9.jpg 91.43KB
  196. plus/datasets/spilt_data/train/labels/
  197. plus/datasets/spilt_data/train/labels/1.txt 53B
  198. plus/datasets/spilt_data/train/labels/10.txt 79B
  199. plus/datasets/spilt_data/train/labels/11.txt 53B
  200. plus/datasets/spilt_data/train/labels/12.txt 27B
  201. plus/datasets/spilt_data/train/labels/13.txt 39B
  202. plus/datasets/spilt_data/train/labels/14.txt 25B
  203. plus/datasets/spilt_data/train/labels/16.txt 52B
  204. plus/datasets/spilt_data/train/labels/18.txt 55B
  205. plus/datasets/spilt_data/train/labels/19.txt 67B
  206. plus/datasets/spilt_data/train/labels/2.txt 55B
  207. plus/datasets/spilt_data/train/labels/3.txt 64B
  208. plus/datasets/spilt_data/train/labels/4.txt 55B
  209. plus/datasets/spilt_data/train/labels/6.txt 63B
  210. plus/datasets/spilt_data/train/labels/7.txt 64B
  211. plus/datasets/spilt_data/train/labels/8.txt 55B
  212. plus/datasets/spilt_data/train/labels/9.txt 61B
  213. plus/datasets/spilt_data/val/
  214. plus/datasets/spilt_data/val/images/
  215. plus/datasets/spilt_data/val/images/20.jpg 30.2KB
  216. plus/datasets/spilt_data/val/images/5.jpg 611.3KB
  217. plus/datasets/spilt_data/val/labels/
  218. plus/datasets/spilt_data/val/labels/20.txt 53B
  219. plus/datasets/spilt_data/val/labels/5.txt 82B
  220. plus/Images/
  221. plus/Images/Segment_Images/
  222. plus/Images/Segment_Images/label_txt/
  223. plus/Images/Segment_Images/label_txt/1.txt 53B
  224. plus/Images/Segment_Images/label_txt/10.txt 80B
  225. plus/Images/Segment_Images/label_txt/11.txt 53B
  226. plus/Images/Segment_Images/label_txt/12.txt 28B
  227. plus/Images/Segment_Images/label_txt/13.txt 53B
  228. plus/Images/Segment_Images/label_txt/14.txt 26B
  229. plus/Images/Segment_Images/label_txt/15.txt 52B
  230. plus/Images/Segment_Images/label_txt/16.txt 53B
  231. plus/Images/Segment_Images/label_txt/17.txt 53B
  232. plus/Images/Segment_Images/label_txt/18.txt 58B
  233. plus/Images/Segment_Images/label_txt/19.txt 79B
  234. plus/Images/Segment_Images/label_txt/2.txt 58B
  235. plus/Images/Segment_Images/label_txt/20.txt 53B
  236. plus/Images/Segment_Images/label_txt/3.txt 78B
  237. plus/Images/Segment_Images/label_txt/4.txt 58B
  238. plus/Images/Segment_Images/label_txt/5.txt 78B
  239. plus/Images/Segment_Images/label_txt/6.txt 68B
  240. plus/Images/Segment_Images/label_txt/7.txt 80B
  241. plus/Images/Segment_Images/label_txt/8.txt 58B
  242. plus/Images/Segment_Images/label_txt/9.txt 64B
  243. plus/json_to_data(mask).py 4.21KB
  244. plus/json_to_dataset.py 3.25KB
  245. plus/mask_to_yolo2.py 1.75KB
  246. plus/mask_to_yolo3(single).py 3.62KB
  247. plus/mask_to_yolotxt.py 2.02KB
  248. plus/RGBA_to_RGB.py 1.4KB
  249. plus/spilt.py 3.15KB
  250. plus/sutady1.py 1.89KB
  251. YOLO/
  252. YOLO/Annotations/
  253. YOLO/JPEGlmages/
  254. YOLO/Models/
  255. YOLO/requirements.txt 1.12KB
  256. YOLO/ultralytics/
  257. YOLO/ultralytics/.git/
  258. YOLO/ultralytics/.git/branches/
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  344. YOLO/ultralytics/docs/en/datasets/
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  347. YOLO/ultralytics/docs/en/datasets/classify/caltech256.md 8KB
  348. YOLO/ultralytics/docs/en/datasets/classify/cifar10.md 8.54KB
  349. YOLO/ultralytics/docs/en/datasets/classify/cifar100.md 7.18KB
  350. YOLO/ultralytics/docs/en/datasets/classify/fashion-mnist.md 7.76KB
  351. YOLO/ultralytics/docs/en/datasets/classify/imagenet.md 8.59KB
  352. YOLO/ultralytics/docs/en/datasets/classify/imagenet10.md 7.61KB
  353. YOLO/ultralytics/docs/en/datasets/classify/imagenette.md 9.08KB
  354. YOLO/ultralytics/docs/en/datasets/classify/imagewoof.md 8.27KB
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  356. YOLO/ultralytics/docs/en/datasets/classify/mnist.md 7.32KB
  357. YOLO/ultralytics/docs/en/datasets/detect/
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  359. YOLO/ultralytics/docs/en/datasets/detect/argoverse.md 8.8KB
  360. YOLO/ultralytics/docs/en/datasets/detect/brain-tumor.md 7.66KB
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  367. YOLO/ultralytics/docs/en/datasets/detect/open-images-v7.md 13.77KB
  368. YOLO/ultralytics/docs/en/datasets/detect/roboflow-100.md 10.68KB
  369. YOLO/ultralytics/docs/en/datasets/detect/signature.md 7.95KB
  370. YOLO/ultralytics/docs/en/datasets/detect/sku-110k.md 9.05KB
  371. YOLO/ultralytics/docs/en/datasets/detect/visdrone.md 9.04KB
  372. YOLO/ultralytics/docs/en/datasets/detect/voc.md 8.51KB
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  1233. YOLO/ultralytics/ultralytics/yolo11n.pt 5.35MB
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[Ultralytics](https://www.ultralytics.com/) [YOLO11](https://github.com/ultralytics/ultralytics) is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLO11 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks. We hope that the resources here will help you get the most out of YOLO. Please browse the Ultralytics Docs for details, raise an issue on GitHub for support, questions, or discussions, become a member of the Ultralytics Discord, Reddit and Forums! To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license). YOLO11 performance plots
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##
Documentation
See below for a quickstart install and usage examples, and see our [Docs](https://docs.ultralytics.com/) for full documentation on training, validation, prediction and deployment.
Install Pip install the ultralytics package including all [requirements](https://github.com/ultralytics/ultralytics/blob/main/pyproject.toml) in a [**Python>=3.8**](https://www.python.org/) environment with [**PyTorch>=1.8**](https://pytorch.org/get-started/locally/). [![PyPI - Version](https://img.shields.io/pypi/v/ultralytics?logo=pypi&logoColor=white)](https://pypi.org/project/ultralytics/) [![Ultralytics Downloads](https://static.pepy.tech/badge/ultralytics)](https://www.pepy.tech/projects/ultralytics) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ultralytics?logo=python&logoColor=gold)](https://pypi.org/project/ultralytics/) ```bash pip install ultralytics ``` For alternative installation methods including [Conda](https://anaconda.org/conda-forge/ultralytics), [Docker](https://hub.docker.com/r/ultralytics/ultralytics), and Git, please refer to the [Quickstart Guide](https://docs.ultralytics.com/quickstart/). [![Conda Version](https://img.shields.io/conda/vn/conda-forge/ultralytics?logo=condaforge)](https://anaconda.org/conda-forge/ultralytics) [![Docker Image Version](https://img.shields.io/docker/v/ultralytics/ultralytics?sort=semver&logo=docker)](https://hub.docker.com/r/ultralytics/ultralytics) [![Ultralytics Docker Pulls](https://img.shields.io/docker/pulls/ultralytics/ultralytics?logo=docker)](https://hub.docker.com/r/ultralytics/ultralytics)
Usage ### CLI YOLO may be used directly in the Command Line Interface (CLI) with a `yolo` command: ```bash yolo predict model=yolo11n.pt source='https://ultralytics.com/images/bus.jpg' ``` `yolo` can be used for a variety of tasks and modes and accepts additional arguments, i.e. `imgsz=640`. See the YOLO [CLI Docs](https://doc
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