Comments (4)
我的想法是用前端的比较图片相似度的库 然后分别截取掉落材料的图片 以及数字,然后再与保存好的材料图片比对。 这里有一个前端的图片识别库的例子:
http://rsmbl.github.io/Resemble.js/
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可能的做法
- 传统的模板匹配。如 SIFT :inkydragon/AkDR: Arknights drops recognize. Using OpenCV with Python.
模板匹配如果不切图计算量较大;切图则分辨率适应性下降,但速度/精度提升极大。算法能否放在前端取决于选择的算法,视情况可使用 opencv.js 或 WebGL 重新实现算法。 - NN。
- 基于 tf 预训练模型(见 ref PPT)
- 基于 YOLOv3 Luke-lujunxian/aktools-backendProcessEngine
NN 无需切图,但训练所需的数据量较大,且训练完毕的模型也比较大,不太可能放在前端。
ref:PPT - GMTC2018 《基于AI的网易UI自动化测试方案与实践》
这个是网易的自动化 UI 测试框架,算是个工业化的产品。其中就涉及图像匹配,包括静态的按钮以及动态的角色的位置识别,值得借鉴。
from frontend-v2.
可能的做法
传统的模板匹配。如 SIFT :inkydragon/AkDR: Arknights drops recognize. Using OpenCV with Python.
模板匹配如果不切图计算量较大;切图则分辨率适应性下降,但速度/精度提升极大。算法能否放在前端取决于选择的算法,视情况可使用 opencv.js 或 WebGL 重新实现算法。NN。
- 基于 tf 预训练模型(见 ref PPT)
- 基于 YOLOv3 Luke-lujunxian/aktools-backendProcessEngine
NN 无需切图,但训练所需的数据量较大,且训练完毕的模型也比较大,不太可能放在前端。ref:PPT - GMTC2018 《基于AI的网易UI自动化测试方案与实践》
这个是网易的自动化 UI 测试框架,算是个工业化的产品。其中就涉及图像匹配,包括静态的按钮以及动态的角色的位置识别,值得借鉴。
L佬和蟹佬在做了,应该用的方法是1(不确定
他们有在考虑用yolo(2)
from frontend-v2.
Proudly closing this issue as this feature has already been running smoothly for 9+ months (and why is this still left open lol).
from frontend-v2.
Related Issues (20)
- [Bug]: 数据库凝胶掉落关卡“玛莉娅・临光 MN-6” 的理智消耗错误 HOT 2
- [Bug]: 表格排序功能无法正确处理无数据的行 HOT 1
- [Suggestion]: 希望可以在刷图规划器中增加一些预设的材料计划
- [Suggestion]: 截图识别支持直接读取剪切板中的图片
- [我不知道这是不是 Bug]: 与 `penguin-stats.cn` 的连接出现问题 HOT 2
- [Bug]: 掉落汇报/素材掉率 作战选择页面 “残阳” 选项仍然为9-11章
- [Bug]: Side Story MN-2 "Extra" Items have incorrect limit HOT 1
- [Bug]: IOS App 无法连接并同步数据,切换主题有机会导致界面语言变为英文(ios默认语言为中文) HOT 4
- [Suggestion]: 界面元素遮挡(素材掉率-按作战中的“限时活动-已结束”挡住了年份) HOT 1
- [Bug]: 停留在网站一段时间后语言会自动变为英文 HOT 1
- [Bug]: 网站在反复多次切换语言时概率不显示翻译的字符串而直接显示原始的键 HOT 1
- [Bug]:
- [Suggestion]:合成配方素材树状图 HOT 1
- [Suggestion]:合成配方素材树状图 HOT 1
- [Bug]: 新章节掉落图无法识别?
- [Bug]: Failed to calculate: 'MaterialPlanning' object has no attribute 'item_array' HOT 1
- [Bug]: Incorrect drop limits on RI-1 HOT 1
- [Bug]: Incorrect drop limits on RI-2 HOT 1
- [Bug]: Newer intermezzi/side story missing from global server
- [Bug]: Incorrect drop limits on GT-4 HOT 1
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