Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
| Date | Stars |
|---|---|
| 2026-07-24 | 260 |
| 2026-07-25 | 260 |
| 2026-07-28 | 260 |
| 2026-07-30 | 260 |
| 2026-08-06 | 260 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# 深度学习 - 微信跳一跳 ### 2018.01.14更新 `simple`目录下增加了`simple.js`，思路同`simple.py`，使用`JavaScript`编写，在安卓上安装`Auto.js`之后运行该脚本即可，好处是直接在手机上运行，不需要连电脑 ### 2018.01.05更新 标注数据增加到1200张图片，并且用更准的`faster_rcnn_inception_v2_coco`模型重新训练了一遍 ### 项目介绍 知乎文章：[https://zhuanlan.zhihu.com/p/32553763](https://zhuanlan.zhihu.com/p/32553763) 感谢[Chao](https://github.com/loveu520)、[奋逗逗](https://github.com/liuzhenhui)对于标注数据做出的贡献 ### 所需环境 - `Python3.6`、`OpenCV2`、`TensorFlow`等 - `adb`，用于调试安卓手机，参考[https://github.com/wangshub/wechat_jump_game](https://github.com/wangshub/wechat_jump_game) ### 文件介绍 `simple`目录中的`simple.py`使用`OpenCV2`检测棋子和目标块的位置，简单粗暴，`simple_ios.py`是对应的IOS版本  `tensorflow`目录包括以下文件： - `wechat_jump_label_map.pbtxt`：物体类别映射文件； - `utils`：提供辅助功能的文件； - `frozen_inference_graph_frcnn_inception_v2_coco.pb`：训练好的物体检测模型，共1200张标注数据，使用`faster_rcnn_inception_v2_coco`训练； - `wechat_auto_jump.py`：自动跳一跳的代码  `label.zip`提供了标注的工具，使用[labelImg](https://github.com/tzutalin/labelImg)进行物体检测标注，使用方法可以参考`物体检测标注说明.pdf` 
Excerpt of 1,079 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ed823382196660bd, topic:tensorflow
matched fp:ed823382196660bd, topic:object-detection
