mirror of
https://github.com/LmeSzinc/StarRailCopilot.git
synced 2024-11-24 17:42:46 +00:00
141 lines
5.0 KiB
Markdown
141 lines
5.0 KiB
Markdown
|
# How to do statistics on item drop rate
|
|||
|
|
|||
|
This document will show how to use `dev_tools/item_statistics.py`
|
|||
|
|
|||
|
## Enable statistics in alas
|
|||
|
|
|||
|
In alas GUI,
|
|||
|
|
|||
|
- set `enable_drop_screenshot` to `yes`, if enabled, alas will add a 1s sleep before screenshot, to avoid capture the flash. There's a flash light when item shows up.
|
|||
|
- set `drop_screenshot_folder` to be the folder you want to save. It is recommended to save it in SSD.
|
|||
|
|
|||
|
After few hours or few days of running, you will get a folder structure like:
|
|||
|
|
|||
|
```
|
|||
|
<your_folder>
|
|||
|
campaign_7_2
|
|||
|
get_items
|
|||
|
158323xxxxxxx.png
|
|||
|
158323xxxxxxx.png
|
|||
|
158323xxxxxxx.png
|
|||
|
get_mission
|
|||
|
get_ship
|
|||
|
mystery
|
|||
|
status
|
|||
|
campaign_10_4_HARD
|
|||
|
get_items
|
|||
|
get_mission
|
|||
|
get_ship
|
|||
|
status
|
|||
|
d3
|
|||
|
get_items
|
|||
|
get_mission
|
|||
|
get_ship
|
|||
|
status
|
|||
|
```
|
|||
|
|
|||
|
Screenshot are named after millesecond timestamp.
|
|||
|
|
|||
|
## Prepare a new environment
|
|||
|
|
|||
|
- Prepare another virtual environment, accoring to `requirements.txt`. But use the GPU version of `mxnet`.
|
|||
|
|
|||
|
I am using GTX1080Ti, and I installed `mxnet-cu80==1.4.1`, `CUDA8.0`, `cuDNN`. Google `mxnet gpu install`, and see how to do in details. You may intall other version of CUDA, and mxnet for that CUDA, because you are using another graphic card.
|
|||
|
|
|||
|
- Look for the cnocr in your virtual environment. Replace site-packages\cnocr\cn_ocr.py line 89
|
|||
|
|
|||
|
```
|
|||
|
mod = mx.mod.Module(symbol=sym, context=mx.cpu(), data_names=data_names, label_names=None)
|
|||
|
```
|
|||
|
|
|||
|
to be:
|
|||
|
|
|||
|
```
|
|||
|
mod = mx.mod.Module(symbol=sym, context=mx.gpu(), data_names=data_names, label_names=None)
|
|||
|
```
|
|||
|
|
|||
|
Now cnocr will run on GPU.
|
|||
|
|
|||
|
You can skip these anyway, and use the same environment as alas, but the OCR will run really slow.
|
|||
|
|
|||
|
- Install tqdm, a package to show progressbar.
|
|||
|
|
|||
|
```
|
|||
|
pip install tqdm
|
|||
|
```
|
|||
|
|
|||
|
## Extract item_template
|
|||
|
|
|||
|
Copy folder `dev_tools\item_template` to the map folder such as `<your_folder>\campaign_7_2`.
|
|||
|
|
|||
|
Change the folder in line 24
|
|||
|
|
|||
|
These template are named in chinese, rename them in English.
|
|||
|
|
|||
|
>**How to a name template image**
|
|||
|
>
|
|||
|
>You should use their full name, such as "138.6mm单装炮Mle1929T3", instead of short name or nickname, such as "DD_gun".
|
|||
|
>
|
|||
|
>If you have same item with different image, use names like `torpedo_part.png`, `torpedo_part_2.png`, they will a classified as torpedo_part
|
|||
|
|
|||
|
Uncomment the part for item extract in dev_tools/item_statistics.py, and run, you will have some new item templates. Here's an example log:
|
|||
|
|
|||
|
```
|
|||
|
1%| | 107/12668 [00:05<10:24, 20.10it/s]2020-06-03 10:39:42.609 | INFO | New item template: 50
|
|||
|
1%| | 158/12668 [00:07<10:42, 19.47it/s]2020-06-03 10:39:45.098 | INFO | New item template: 51
|
|||
|
2%|▏ | 207/12668 [00:10<10:33, 19.66it/s]2020-06-03 10:39:47.772 | INFO | New item template: 52
|
|||
|
2%|▏ | 215/12668 [00:10<11:20, 18.29it/s]2020-06-03 10:39:48.304 | INFO | New item template: 53
|
|||
|
100%|██████████| 12668/12668 [10:33<00:00, 19.99it/s]
|
|||
|
```
|
|||
|
|
|||
|
Rename those new templates.
|
|||
|
|
|||
|
If you find some items haven't been extracted, try use line 140, instead of 141.
|
|||
|
|
|||
|
## Final statistic
|
|||
|
|
|||
|
Uncomment the part for final statistic, configure the csv file you wang to save.
|
|||
|
|
|||
|
The ocr model may not works fine in EN.
|
|||
|
|
|||
|
Here's an example log:
|
|||
|
|
|||
|
```
|
|||
|
2020-06-03 12:23:55.355 | INFO | [ENEMY_GENRE 0.007s] 中型侦查舰队
|
|||
|
2020-06-03 12:23:55.363 | INFO | [Amount_ocr 0.009s] [1, 1, 22]
|
|||
|
100%|█████████▉| 14916/14919 [20:32<00:00, 13.20it/s]2020-06-03 12:23:55.442 | INFO | [ENEMY_GENRE 0.007s] 大型航空舰队
|
|||
|
2020-06-03 12:23:55.455 | INFO | [Amount_ocr 0.013s] [1, 1, 1, 17]
|
|||
|
2020-06-03 12:23:55.539 | INFO | [ENEMY_GENRE 0.007s] 敌方旗舰
|
|||
|
2020-06-03 12:23:55.549 | INFO | [Amount_ocr 0.010s] [1, 2, 1, 63]
|
|||
|
100%|█████████▉| 14918/14919 [20:33<00:00, 12.35it/s]2020-06-03 12:23:55.623 | INFO | [ENEMY_GENRE 0.007s] 精英舰队
|
|||
|
2020-06-03 12:23:55.633 | INFO | [Amount_ocr 0.010s] [1, 1, 1, 17]
|
|||
|
100%|██████████| 14919/14919 [20:33<00:00, 12.10it/s]
|
|||
|
```
|
|||
|
|
|||
|
Now you got a csv file, formated to be:
|
|||
|
|
|||
|
```
|
|||
|
<get_item_timestamp>, <battle_status_timestamp>, <enemy_genre>, <item_name>, <item_amount>
|
|||
|
```
|
|||
|
|
|||
|
like this:
|
|||
|
|
|||
|
```
|
|||
|
1590271317900,1590271315841,中型主力舰队,主炮部件T3,1
|
|||
|
1590271317900,1590271315841,中型主力舰队,物资,23
|
|||
|
1590271359374,1590271357251,小型侦查舰队,通用部件T1,1
|
|||
|
1590271359374,1590271357251,小型侦查舰队,鱼雷部件T2,1
|
|||
|
1590271359374,1590271357251,小型侦查舰队,物资,13
|
|||
|
1590271415308,1590271413207,敌方旗舰,彗星,1
|
|||
|
1590271415308,1590271413207,敌方旗舰,通用部件T3,1
|
|||
|
1590271415308,1590271413207,敌方旗舰,科技箱T1,1
|
|||
|
1590271415308,1590271413207,敌方旗舰,物资,42
|
|||
|
1590271415308,1590271413207,敌方旗舰,_比萨研发物资,1
|
|||
|
1590271415308,1590271413207,敌方旗舰,_鸢尾之印,1
|
|||
|
```
|
|||
|
|
|||
|
You can open it in Excel or load it into database.
|
|||
|
|
|||
|
## Improvement
|
|||
|
|
|||
|
These code is running on single thread, you can try adding multiprocess to speed up. I didn't do that because it's still acceptable (20it/s without ocr, 12it/s with ocr)
|