ZIPyolov3/////////// 1.02MB

jing_h21

资源文件列表:

yolov3-master.zip 大约有163个文件
  1. yolov3-master/
  2. yolov3-master/.dockerignore 3.61KB
  3. yolov3-master/.github/
  4. yolov3-master/.github/ISSUE_TEMPLATE/
  5. yolov3-master/.github/ISSUE_TEMPLATE/bug-report.yml 2.9KB
  6. yolov3-master/.github/ISSUE_TEMPLATE/config.yml 399B
  7. yolov3-master/.github/ISSUE_TEMPLATE/feature-request.yml 1.79KB
  8. yolov3-master/.github/ISSUE_TEMPLATE/question.yml 1.17KB
  9. yolov3-master/.github/dependabot.yml 649B
  10. yolov3-master/.github/workflows/
  11. yolov3-master/.github/workflows/ci-testing.yml 5.51KB
  12. yolov3-master/.github/workflows/cla.yml 1.57KB
  13. yolov3-master/.github/workflows/codeql-analysis.yml 2.07KB
  14. yolov3-master/.github/workflows/docker.yml 1.55KB
  15. yolov3-master/.github/workflows/format.yml 1.12KB
  16. yolov3-master/.github/workflows/greetings.yml 5.36KB
  17. yolov3-master/.github/workflows/links.yml 2.44KB
  18. yolov3-master/.github/workflows/stale.yml 2.31KB
  19. yolov3-master/.gitignore 3.9KB
  20. yolov3-master/CITATION.cff 399B
  21. yolov3-master/CONTRIBUTING.md 4.88KB
  22. yolov3-master/LICENSE 33.71KB
  23. yolov3-master/README.md 41.29KB
  24. yolov3-master/README.zh-CN.md 41.03KB
  25. yolov3-master/benchmarks.py 13.71KB
  26. yolov3-master/classify/
  27. yolov3-master/classify/predict.py 11.76KB
  28. yolov3-master/classify/train.py 15.97KB
  29. yolov3-master/classify/tutorial.ipynb 101.19KB
  30. yolov3-master/classify/val.py 8KB
  31. yolov3-master/data/
  32. yolov3-master/data/Argoverse.yaml 2.66KB
  33. yolov3-master/data/GlobalWheat2020.yaml 1.84KB
  34. yolov3-master/data/ImageNet.yaml 18.42KB
  35. yolov3-master/data/SKU-110K.yaml 2.28KB
  36. yolov3-master/data/VisDrone.yaml 2.9KB
  37. yolov3-master/data/coco.yaml 2.43KB
  38. yolov3-master/data/coco128-seg.yaml 1.85KB
  39. yolov3-master/data/coco128.yaml 1.83KB
  40. yolov3-master/data/hyps/
  41. yolov3-master/data/hyps/hyp.Objects365.yaml 671B
  42. yolov3-master/data/hyps/hyp.VOC.yaml 1.13KB
  43. yolov3-master/data/hyps/hyp.no-augmentation.yaml 1.61KB
  44. yolov3-master/data/hyps/hyp.scratch-high.yaml 1.61KB
  45. yolov3-master/data/hyps/hyp.scratch-low.yaml 1.62KB
  46. yolov3-master/data/hyps/hyp.scratch-med.yaml 1.62KB
  47. yolov3-master/data/images/
  48. yolov3-master/data/images/bus.jpg 476.01KB
  49. yolov3-master/data/images/zidane.jpg 164.99KB
  50. yolov3-master/data/objects365.yaml 8.98KB
  51. yolov3-master/data/scripts/
  52. yolov3-master/data/scripts/download_weights.sh 641B
  53. yolov3-master/data/scripts/get_coco.sh 1.53KB
  54. yolov3-master/data/scripts/get_coco128.sh 619B
  55. yolov3-master/data/scripts/get_imagenet.sh 1.63KB
  56. yolov3-master/data/voc.yaml 3.41KB
  57. yolov3-master/data/xView.yaml 5.04KB
  58. yolov3-master/detect.py 22.55KB
  59. yolov3-master/export.py 67.78KB
  60. yolov3-master/hubconf.py 21.73KB
  61. yolov3-master/models/
  62. yolov3-master/models/__init__.py
  63. yolov3-master/models/common.py 48.6KB
  64. yolov3-master/models/experimental.py 5.03KB
  65. yolov3-master/models/hub/
  66. yolov3-master/models/hub/anchors.yaml 3.26KB
  67. yolov3-master/models/hub/yolov5-bifpn.yaml 1.41KB
  68. yolov3-master/models/hub/yolov5-fpn.yaml 1.2KB
  69. yolov3-master/models/hub/yolov5-p2.yaml 1.66KB
  70. yolov3-master/models/hub/yolov5-p34.yaml 1.21KB
  71. yolov3-master/models/hub/yolov5-p6.yaml 1.71KB
  72. yolov3-master/models/hub/yolov5-p7.yaml 2.09KB
  73. yolov3-master/models/hub/yolov5-panet.yaml 1.39KB
  74. yolov3-master/models/hub/yolov5l6.yaml 1.79KB
  75. yolov3-master/models/hub/yolov5m6.yaml 1.79KB
  76. yolov3-master/models/hub/yolov5n6.yaml 1.79KB
  77. yolov3-master/models/hub/yolov5s-LeakyReLU.yaml 1.48KB
  78. yolov3-master/models/hub/yolov5s-ghost.yaml 1.46KB
  79. yolov3-master/models/hub/yolov5s-transformer.yaml 1.42KB
  80. yolov3-master/models/hub/yolov5s6.yaml 1.79KB
  81. yolov3-master/models/hub/yolov5x6.yaml 1.79KB
  82. yolov3-master/models/segment/
  83. yolov3-master/models/segment/yolov5l-seg.yaml 1.39KB
  84. yolov3-master/models/segment/yolov5m-seg.yaml 1.4KB
  85. yolov3-master/models/segment/yolov5n-seg.yaml 1.4KB
  86. yolov3-master/models/segment/yolov5s-seg.yaml 1.4KB
  87. yolov3-master/models/segment/yolov5x-seg.yaml 1.4KB
  88. yolov3-master/models/tf.py 30.87KB
  89. yolov3-master/models/yolo.py 19.78KB
  90. yolov3-master/models/yolov3-spp.yaml 1.55KB
  91. yolov3-master/models/yolov3-tiny.yaml 1.22KB
  92. yolov3-master/models/yolov3.yaml 1.54KB
  93. yolov3-master/models/yolov5l.yaml 1.38KB
  94. yolov3-master/models/yolov5m.yaml 1.39KB
  95. yolov3-master/models/yolov5n.yaml 1.39KB
  96. yolov3-master/models/yolov5s.yaml 1.39KB
  97. yolov3-master/models/yolov5x.yaml 1.39KB
  98. yolov3-master/pyproject.toml 5.18KB
  99. yolov3-master/requirements.txt 1.55KB
  100. yolov3-master/segment/
  101. yolov3-master/segment/predict.py 15.83KB
  102. yolov3-master/segment/train.py 34.34KB
  103. yolov3-master/segment/tutorial.ipynb 42.41KB
  104. yolov3-master/segment/val.py 23.55KB
  105. yolov3-master/train.py 39.29KB
  106. yolov3-master/tutorial.ipynb 40.02KB
  107. yolov3-master/utils/
  108. yolov3-master/utils/__init__.py 3.25KB
  109. yolov3-master/utils/activations.py 4.93KB
  110. yolov3-master/utils/augmentations.py 18.21KB
  111. yolov3-master/utils/autoanchor.py 7.75KB
  112. yolov3-master/utils/autobatch.py 3.02KB
  113. yolov3-master/utils/aws/
  114. yolov3-master/utils/aws/__init__.py
  115. yolov3-master/utils/aws/mime.sh 780B
  116. yolov3-master/utils/aws/resume.py 1.21KB
  117. yolov3-master/utils/aws/userdata.sh 1.22KB
  118. yolov3-master/utils/callbacks.py 2.66KB
  119. yolov3-master/utils/dataloaders.py 57.17KB
  120. yolov3-master/utils/docker/
  121. yolov3-master/utils/docker/Dockerfile 2.6KB
  122. yolov3-master/utils/docker/Dockerfile-arm64 1.63KB
  123. yolov3-master/utils/docker/Dockerfile-cpu 1.88KB
  124. yolov3-master/utils/downloads.py 5.04KB
  125. yolov3-master/utils/flask_rest_api/
  126. yolov3-master/utils/flask_rest_api/README.md 1.67KB
  127. yolov3-master/utils/flask_rest_api/example_request.py 365B
  128. yolov3-master/utils/flask_rest_api/restapi.py 1.53KB
  129. yolov3-master/utils/general.py 49.75KB
  130. yolov3-master/utils/google_app_engine/
  131. yolov3-master/utils/google_app_engine/Dockerfile 821B
  132. yolov3-master/utils/google_app_engine/additional_requirements.txt 264B
  133. yolov3-master/utils/google_app_engine/app.yaml 219B
  134. yolov3-master/utils/loggers/
  135. yolov3-master/utils/loggers/__init__.py 18.03KB
  136. yolov3-master/utils/loggers/clearml/
  137. yolov3-master/utils/loggers/clearml/README.md 10.55KB
  138. yolov3-master/utils/loggers/clearml/__init__.py
  139. yolov3-master/utils/loggers/clearml/clearml_utils.py 7.59KB
  140. yolov3-master/utils/loggers/clearml/hpo.py 5.17KB
  141. yolov3-master/utils/loggers/comet/
  142. yolov3-master/utils/loggers/comet/README.md 10.56KB
  143. yolov3-master/utils/loggers/comet/__init__.py 21.5KB
  144. yolov3-master/utils/loggers/comet/comet_utils.py 4.71KB
  145. yolov3-master/utils/loggers/comet/hpo.py 6.76KB
  146. yolov3-master/utils/loggers/comet/optimizer_config.json 2.37KB
  147. yolov3-master/utils/loggers/wandb/
  148. yolov3-master/utils/loggers/wandb/__init__.py
  149. yolov3-master/utils/loggers/wandb/wandb_utils.py 7.96KB
  150. yolov3-master/utils/loss.py 10.91KB
  151. yolov3-master/utils/metrics.py 15.06KB
  152. yolov3-master/utils/plots.py 19.7KB
  153. yolov3-master/utils/segment/
  154. yolov3-master/utils/segment/__init__.py
  155. yolov3-master/utils/segment/augmentations.py 3.66KB
  156. yolov3-master/utils/segment/dataloaders.py 13.17KB
  157. yolov3-master/utils/segment/general.py 5.8KB
  158. yolov3-master/utils/segment/loss.py 8.96KB
  159. yolov3-master/utils/segment/metrics.py 5.66KB
  160. yolov3-master/utils/segment/plots.py 6.45KB
  161. yolov3-master/utils/torch_utils.py 21KB
  162. yolov3-master/utils/triton.py 3.73KB
  163. yolov3-master/val.py 29.86KB

资源介绍:

yolov3///////////
<div align="center"> <p> <a align="center" href="https://ultralytics.com/yolov3" target="_blank"> <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov3/banner-yolov3.png"></a> </p> [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/) | [啶灌た啶ㄠ啶︵](https://docs.ultralytics.com/hi/) | [丕賱毓乇亘賷丞](https://docs.ultralytics.com/ar/) <div> <a href="https://github.com/ultralytics/yolov3/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov3/actions/workflows/ci-testing.yml/badge.svg" alt="YOLOv3 CI"></a> <a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv3 Citation"></a> <a href="https://hub.docker.com/r/ultralytics/yolov3"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov3?logo=docker" alt="Docker Pulls"></a> <a href="https://ultralytics.com/discord"><img alt="Discord" src="https://img.shields.io/discord/1089800235347353640?logo=discord&logoColor=white&label=Discord&color=blue"></a> <a href="https://community.ultralytics.com"><img alt="Ultralytics Forums" src="https://img.shields.io/discourse/users?server=https%3A%2F%2Fcommunity.ultralytics.com&logo=discourse&label=Forums&color=blue"></a> <br> <a href="https://bit.ly/yolov5-paperspace-notebook"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Run on Gradient"></a> <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> <a href="https://www.kaggle.com/ultralytics/yolov5"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> </div> <br> YOLOv3 馃殌 is the world's most loved vision AI, representing <a href="https://ultralytics.com">Ultralytics</a> 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 YOLOv3. Please browse the YOLOv3 <a href="https://docs.ultralytics.com/yolov5">Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/yolov3/issues/new/choose">GitHub</a> for support, and join our <a href="https://ultralytics.com/discord">Discord</a> community for questions and discussions! To request an Enterprise License please complete the form at [Ultralytics Licensing](https://ultralytics.com/license). <div align="center"> <a href="https://github.com/ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="Ultralytics GitHub"></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%"> <a href="https://www.linkedin.com/company/ultralytics/"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="Ultralytics LinkedIn"></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%"> <a href="https://twitter.com/ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="2%" alt="Ultralytics Twitter"></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%"> <a href="https://youtube.com/ultralytics?sub_confirmation=1"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="2%" alt="Ultralytics YouTube"></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%"> <a href="https://www.tiktok.com/@ultralytics"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="2%" alt="Ultralytics TikTok"></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%"> <a href="https://ultralytics.com/bilibili"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-bilibili.png" width="2%" alt="Ultralytics BiliBili"></a> <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%"> <a href="https://ultralytics.com/discord"><img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-discord.png" width="2%" alt="Ultralytics Discord"></a> </div> </div> <br> ## <div align="center">YOLOv8 馃殌 NEW</div> 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 ``` <div align="center"> <a href="https://ultralytics.com/yolov8" target="_blank"> <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/yolo-comparison-plots.png"></a> </div> ## <div align="center">Documentation</div> See the [YOLOv3 Docs](https://docs.ultralytics.com) for full documentation on training, testing and deployment. See below for quickstart examples. <details open> <summary>Install</summary> Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a [**Python>=3.7.0**](https://www.python.org/) environment, including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). ```bash git clone https://github.com/ultralytics/yolov3 # clone cd yolov3 pip install -r requirements.txt # install ``` </details> <details> <summary>Inference</summary> YOLOv3 [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 YOLOv3 [release](https://github.com/ultralytics/yolov5/releases). ```python import torch # Model model = torch.hub.load("ultralytics/yolov3", "yolov3") # 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. ``` </details> <details> <summary>Inference with detect.py</summary> `detect.py` runs inference on a variety of sources, downloading [models](https://github.com/ultralytics/yolov5/tree/master/models) automatically from the latest YOLOv3 [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 screen # screenshot path/ # directory list.txt
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