更新 Yolo
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歡迎使用 Wiki!
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# YOLO
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### 若電腦沒有顯卡,則可以先用colab的方式進行一個簡單demo
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### 建議都試看看如何使用Yolo,可以套用到很多場景
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#### 若對AI有興趣的,可以去了解CNN、RNN、GAN、DON、DRL、LLM
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##
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# Yolo V5
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### 可先透過YOLO的github進行查詢,確認所需的環境需求
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### V5 [連接](https://github.com/ultralytics/yolov5)
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由文件中可知所需環境:
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* Python 3.8以上
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* Pytorch 1.8以上
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%871.png)
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### 下載V5檔案 [連接](https://github.com/ultralytics/yolov5)
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1. 按下Code
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2. 按下Download ZIP
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3. 解壓縮剛剛下載的檔案
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%872.png)
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### 環境安裝
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* 為了同一使用規範,這邊一律採用WinPython的方式進行
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* 可透過提供的環境繼續使用,若要自行架設,繼續往下觀看
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* Winpython[連接](http://140.125.21.65:500/sharing/hS347f5na)
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* 選擇所需要的即可,之後安裝V5是採用3.8,V8採用3.10
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%873.png)
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安裝好WinPython後,打開小黑框
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%874.png)
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### 於指令中輸入 pip list
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%875.png)
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### 尋找torch
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若torch版本號後沒有cu的之類的 直接卸載
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`pip uninstall torch`
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接著按Y 確認刪除
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`pip uninstall torchaudio`
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接著按Y 確認刪除
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`pip uninstall torchvision`
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接著按Y 確認刪除
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%876.png)
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### 上Pytorch的官網,找尋歷史安裝包[link](https://pytorch.org/get-started/previous-versions/):
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%877.png)
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於指令中輸入
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`pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html`
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%878.png)
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於指令中輸入 pip list 確認
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%879.png)
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### 遇到問題
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若出現:
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8710.png)
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輸入 `pip install opencv-python`
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若出現:
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8711.png)
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輸入 `pip install ultralytics`
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### 測試環境
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1. 根據我給的teching_test的資料夾
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2. 使用指令到達此資料夾 cd D:\…….\teaching_test
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8712.png)
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3. 輸入
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`python test_yolo.py `
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4. 若能成功運行,並顯示以下畫面,則此環境就能使用了
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8713.png)
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##
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# Yolo V8
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### 可先透過YOLO的github進行查詢,確認所需的環境需求
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### V8 [連接](https://github.com/ultralytics/ultralytics)
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由文件中可知所需環境:
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* Python 3.8以上
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* Pytorch 1.8以上
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8714.png)
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### 環境安裝
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### 上Pytorch的官網,找尋歷史安裝包[link](https://pytorch.org/get-started/previous-versions/):
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8715.png)
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###
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安裝方式與V5差不多,最終確認
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8716.png)
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### 測試環境
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1. 根據我給的teching_test的資料夾
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2. 使用指令到達此資料夾 cd D:\…….\teaching_test
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8717.png)
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3. 輸入
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`python test_yolo.py `
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8718.png)
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4. 若能成功運行,並顯示以下畫面,則此環境就能使用了
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8719.png)
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## 若安裝許久都無法順利運行,或許是環境有未下載到的,可以直接安裝我提供的環境進行測試。目前實測2-3台,都沒有太多問題。
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網址 -[140.125.21.65:500]( http://140.125.21.65:500/)
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帳號 : VIP125
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密碼 : Aa125125
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![](http://140.125.21.65:8418/Education/Python/raw/branch/master/Yolo/img/%E5%9C%96%E7%89%8720.png)
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