下载资源人工智能资源详情
YOLO数字识别程序+树莓派依赖包.zip
大小:98.67MB
价格:15积分
下载量:0
评分:
5.0
上传者:2301_81315771
更新日期:2025-09-22

笔者的数字识别模型、树莓派上所需安装的依赖包（包括onnxruntime依赖）以及YOLOv5-lite1.4版本的源码

资源文件列表(大概)

文件名
大小
YOLOv5-Lite-1.4/
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YOLOv5-Lite-1.4/.idea/
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YOLOv5-Lite-1.4/.idea/.gitignore
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YOLOv5-Lite-1.4/.idea/.name
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YOLOv5-Lite-1.4/.idea/YOLOv5-Lite-1.4.iml
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YOLOv5-Lite-1.4/.idea/inspectionProfiles/
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YOLOv5-Lite-1.4/.idea/inspectionProfiles/profiles_settings.xml
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YOLOv5-Lite-1.4/.idea/misc.xml
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YOLOv5-Lite-1.4/.idea/modules.xml
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YOLOv5-Lite-1.4/.idea/workspace.xml
2.72KB
YOLOv5-Lite-1.4/YOLOv5-Lite/
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YOLOv5-Lite-1.4/YOLOv5-Lite/LICENSE
34.96KB
YOLOv5-Lite-1.4/YOLOv5-Lite/README.md
12.61KB
YOLOv5-Lite-1.4/YOLOv5-Lite/__pycache__/
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YOLOv5-Lite-1.4/YOLOv5-Lite/__pycache__/test.cpython-312.pyc
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/README.md
1.76KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/build.gradle
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/AndroidManifest.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/ic_launcher-playstore.png
175.05KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/java/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/java/ncnn/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/java/ncnn/v5lite/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/java/ncnn/v5lite/demo/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/java/ncnn/v5lite/demo/MainActivity.java
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/java/ncnn/v5lite/demo/Ncnnv5lite.java
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/CMakeLists.txt
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/ndkcamera.cpp
24.29KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/ndkcamera.h
2.35KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/yolov5.cpp
20.5KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/yolov5.h
1.86KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/jni/yolov5ncnn.cpp
6.77KB
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/drawable/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/drawable/ic_launcher_background.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/layout/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/layout/main.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-anydpi-v26/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-anydpi-v26/ic_launcher.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-anydpi-v26/ic_launcher_round.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-hdpi/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-hdpi/ic_launcher.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-hdpi/ic_launcher_foreground.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-hdpi/ic_launcher_round.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-mdpi/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-mdpi/ic_launcher.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-mdpi/ic_launcher_foreground.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-mdpi/ic_launcher_round.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xhdpi/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xhdpi/ic_launcher.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xhdpi/ic_launcher_foreground.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xhdpi/ic_launcher_round.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxhdpi/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxhdpi/ic_launcher.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxhdpi/ic_launcher_foreground.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxhdpi/ic_launcher_round.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxxhdpi/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxxhdpi/ic_launcher.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxxhdpi/ic_launcher_foreground.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/mipmap-xxxhdpi/ic_launcher_round.png
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/values/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/app/src/main/res/values/strings.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/build/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/build/intermediates/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/build/intermediates/lint-cache/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/build/intermediates/lint-cache/sdk-registry.xml/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/build/intermediates/lint-cache/sdk-registry.xml/sdk-registry.xml
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/build.gradle
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/gradle/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/gradle/wrapper/
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/gradle/wrapper/gradle-wrapper.jar
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/gradle/wrapper/gradle-wrapper.properties
238B
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/gradlew
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/gradlew.bat
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YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/local.properties
476B
YOLOv5-Lite-1.4/YOLOv5-Lite/android_demo/ncnn-android-v5lite/settings.gradle
16B
YOLOv5-Lite-1.4/YOLOv5-Lite/best.onnx
5.97MB
YOLOv5-Lite-1.4/YOLOv5-Lite/best.pt
3.2MB
YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/CMakeLists.txt
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/README.md
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/include/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/include/Yolo.h
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/include/util.h
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/out.jpg
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/src/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/src/Yolo.cpp
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/src/main.cpp
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/src/util.cpp
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/mnn/test.jpg
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/README.md
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/images/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/model_zoo/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/model_zoo/yolov5-lite-int8.param
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/model_zoo/yolov5-lite.param
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/ncnn/v5lite-s.cpp
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/onnxruntime/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/onnxruntime/coco.names
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/onnxruntime/v5lite.cpp
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/tengine/
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YOLOv5-Lite-1.4/YOLOv5-Lite/cpp_demo/tengine/yolov5s-lite_out.jpg
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/activations.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/general.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/loss.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/metrics.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/plots.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/torch_utils.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/wandb_logging/
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/wandb_logging/log_dataset.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/utils/wandb_logging/wandb_utils.py
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YOLOv5-Lite-1.4/YOLOv5-Lite/v5lite-s.pt
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YOLOv5-Lite-1.4/YOLOv5-Lite/说明.txt
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树莓派Python依赖.zip
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说明.txt
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资源内容介绍

所有在树莓派上需要的依赖都在这里，还有笔者训练好的模型
# YOLOv5-Lite：Lighter, faster and easier to deploy ![](https://zenodo.org/badge/DOI/10.5281/zenodo.5241425.svg)![image](https://user-images.githubusercontent.com/82716366/135564164-3ec169c8-93a7-4ea3-b0dc-40f1059601ef.png)Perform a series of ablation experiments on yolov5 to make it lighter (smaller Flops, lower memory, and fewer parameters) and faster (add shuffle channel, yolov5 head for channel reduce. It can infer at least 10+ FPS On the Raspberry Pi 4B when input the frame with 320×320) and is easier to deploy (removing the Focus layer and four slice operations, reducing the model quantization accuracy to an acceptable range).## Comparison of ablation experiment results ID|Model | Input_size|Flops| Params | Size（M） |Map@0.5|Map@.5:0.95 :-----:|:-----:|:-----:|:----------:|:----:|:----:|:----:|:----:|001| yolo-fastest| 320×320|0.25G|0.35M|1.4| 24.4| -002| YOLOv5-Lite<sub>e</sub><sup>ours</sup>|320×320|0.73G|0.78M|1.7| 35.1|-|003| NanoDet-m| 320×320| 0.72G|0.95M|1.8|- |20.6004| yolo-fastest-xl| 320×320|0.72G|0.92M|3.5| 34.3| -005| YOLOX<sub>Nano</sub>|416×416|1.08G|0.91M|7.3(fp32)| -|25.8|006| yolov3-tiny| 416×416| 6.96G|6.06M|23.0| 33.1|16.6007| yolov4-tiny| 416×416| 5.62G|8.86M| 33.7|40.2|21.7008| YOLOv5-Lite<sub>s</sub><sup>ours</sup>| 416×416|1.66G |1.64M|3.4| 42.0|25.2009| YOLOv5-Lite<sub>c</sub><sup>ours</sup>| 512×512|5.92G |4.57M|9.2| 50.9|32.5| 010| NanoDet-EfficientLite2| 512×512| 7.12G|4.71M|18.3|- |32.6011| YOLOv5s(6.0)| 640×640| 16.5G|7.23M|14.0| 56.0|37.2012| YOLOv5-Lite<sub>g</sub><sup>ours</sup>| 640×640|15.6G |5.39M|10.9| 57.6|39.1| See the wiki: https://github.com/ppogg/YOLOv5-Lite/wiki/Test-the-map-of-models-about-coco## Comparison on different platformsEquipment|Computing backend|System|Input|Framework|v5lite-e|v5lite-s|v5lite-c|v5lite-g|YOLOv5s:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:Inter|@i5-10210U|window(x86)|640×640|openvino|-|-|46ms|-|131msNvidia|@RTX 2080Ti|Linux(x86)|640×640|torch|-|-|-|15ms|14msRedmi K30|@Snapdragon 730G|Android(armv8)|320×320|ncnn|27ms|38ms|-|-|163msXiaomi 10|@Snapdragon 865|Android(armv8)|320×320|ncnn|10ms|14ms|-|-|163msRaspberrypi 4B|@ARM Cortex-A72|Linux(arm64)|320×320|ncnn|-|84ms|-|-|371msRaspberrypi 4B|@ARM Cortex-A72|Linux(arm64)|320×320|mnn|-|76ms|-|-|356ms* The above is a 4-thread test benchmark* Raspberrypi 4B enable bf16s optimization，[Raspberrypi 64 Bit OS](http://downloads.raspberrypi.org/raspios_arm64/images/raspios_arm64-2020-08-24/)### qq交流群：993965802## ·Model Zoo· #### @v5lite-e:Model|Size|Backbone|Head|Framework|Design for:---:|:---:|:---:|:---:|:---:|:---v5Lite-e.pt|1.7m|shufflenetv2（Megvii）|v5Litee-head|Pytorch|Arm-cpuv5Lite-e.bin<br />v5Lite-e.param|1.7m|shufflenetv2|v5Litee-head|ncnn|Arm-cpuv5Lite-e-int8.bin<br />v5Lite-e-int8.param|0.9m|shufflenetv2|v5Litee-head|ncnn|Arm-cpuv5Lite-e-fp32.mnn|3.0m|shufflenetv2|v5Litee-head|mnn|Arm-cpuv5Lite-e-fp32.tnnmodel<br />v5Lite-e-fp32.tnnproto|2.9m|shufflenetv2|v5Litee-head|tnn|arm-cpu#### @v5lite-s:Model|Size|Backbone|Head|Framework|Design for:---:|:---:|:---:|:---:|:---:|:---v5Lite-s.pt|3.4m|shufflenetv2（Megvii）|v5Lites-head|Pytorch|Arm-cpuv5Lite-s.bin<br />v5Lite-s.param|3.3m|shufflenetv2|v5Lites-head|ncnn|Arm-cpuv5Lite-s-int8.bin<br />v5Lite-s-int8.param|1.7m|shufflenetv2|v5Lites-head|ncnn|Arm-cpuv5Lite-s.mnn|3.3m|shufflenetv2|v5Lites-head|mnn|Arm-cpuv5Lite-s-int4.mnn|987k|shufflenetv2|v5Lites-head|mnn|Arm-cpuv5Lite-s-fp16.bin<br />v5Lite-s-fp16.xml|3.4m|shufflenetv2|v5Lites-head|openvivo|x86-cpuv5Lite-s-fp32.bin<br />v5Lite-s-fp32.xml|6.8m|shufflenetv2|v5Lites-head|openvivo|x86-cpuv5Lite-s-fp16.tflite|3.3m|shufflenetv2|v5Lites-head|tflite|arm-cpuv5Lite-s-fp32.tflite|6.7m|shufflenetv2|v5Lites-head|tflite|arm-cpuv5Lite-s-int8.tflite|1.8m|shufflenetv2|v5Lites-head|tflite|arm-cpu#### @v5lite-c:Model|Size|Backbone|Head|Framework|Design for:---:|:---:|:---:|:---:|:---:|:---:v5Lite-c.pt|9m|PPLcnet（Baidu）|v5Litec-head|Pytorch|x86-cpu / x86-vpuv5Lite-c.bin<br />v5Lite-c.xml|8.7m|PPLcnet|v5Litec-head|openvivo|x86-cpu / x86-vpu#### @v5lite-g:Model|Size|Backbone|Head|Framework|Design for:---:|:---:|:---:|:---:|:---:|:---:v5Lite-g.pt|10.9m|Repvgg（Tsinghua）|v5Liteg-head|Pytorch|x86-gpu / arm-gpu / arm-npuv5Lite-g-int8.engine|8.5m|Repvgg|v5Liteg-head|Tensorrt|x86-gpu / arm-gpu / arm-npuv5lite-g-int8.tmfile|8.7m|Repvgg|v5Liteg-head|Tengine| arm-npu#### Download Link：> - [ ] `v5lite-e.pt`: | [Baidu Drive](https://pan.baidu.com/s/1bjXo7KIFkOnB3pxixHeMPQ) | [Google Drive](https://drive.google.com/file/d/1_DvT_qjznuE-ev_pDdGKwRV3MjZ3Zos8/view?usp=sharing) |<br> >> |──────`ncnn-fp16`: | [Baidu Drive]() | [Google Drive](https://drive.google.com/drive/folders/1w4mThJmqjhT1deIXMQAQ5xjWI3JNyzUl?usp=sharing) |<br> >> |──────`ncnn-int8`: | [Baidu Drive]() | [Google Drive](https://drive.google.com/drive/folders/1YNtNVWlRqN8Dwc_9AtRkN0LFkDeJ92gN?usp=sharing) |<br> >> |──────`mnn-fp32`: | [Baidu Drive]() | [Google Drive](https://drive.google.com/drive/folders/1Kha3vQF-7qc5i-GFryInStgTFisGL5vq?usp=sharing) |<br> >> └──────tnn-fp32`: | [Baidu Drive]() | [Google Drive](https://drive.google.com/drive/folders/1VWmI2BC9MjH7BsrOz4VlSDVnZMXaxGOE?usp=sharing) |<br> > - [ ] `v5lite-s.pt`: | [Baidu Drive](https://pan.baidu.com/s/1j0n0K1kqfv1Ouwa2QSnzCQ) | [Google Drive](https://drive.google.com/file/d/1ccLTmGB5AkKPjDOyxF3tW7JxGWemph9f/view?usp=sharing) |<br> >> |──────`ncnn-fp16`: | [Baidu Drive](https://pan.baidu.com/s/1kWtwx1C0OTTxbwqJyIyXWg) | [Google Drive](https://drive.google.com/drive/folders/1w4mThJmqjhT1deIXMQAQ5xjWI3JNyzUl?usp=sharing) |<br> >> |──────`ncnn-int8`: | [Baidu Drive](https://pan.baidu.com/s/1QX6-oNynrW-f3i0P0Hqe4w) | [Google Drive](https://drive.google.com/drive/folders/1YNtNVWlRqN8Dwc_9AtRkN0LFkDeJ92gN?usp=sharing) |<br> >> |──────`mnn-fp16`: | [Baidu Drive](https://pan.baidu.com/s/12lOtPTl4xujWm5BbFJh3zA) | [Google Drive](https://drive.google.com/drive/folders/1PpFoZ4b8mVs1GmMxgf0WUtXUWaGK_JZe?usp=sharing) |<br> >> |──────`mnn-int4`: | [Baidu Drive](https://pan.baidu.com/s/11fbjFi18xkq4ltAKUKDOCA) | [Google Drive](https://drive.google.com/drive/folders/1mSU8g94c77KKsHC-07p5V3tJOZYPQ-g6?usp=sharing) |<br> >> └──────`tengine-fp32`: | [Baidu Drive](https://pan.baidu.com/s/123r630O8Fco7X59wFU1crA) | [Google Drive](https://drive.google.com/drive/folders/1VWmI2BC9MjH7BsrOz4VlSDVnZMXaxGOE?usp=sharing) |<br> > - [ ] `v5lite-c.pt`: [Baidu Drive](https://pan.baidu.com/s/1obs6uRB79m8e3uASVR6P1A) | [Google Drive](https://drive.google.com/file/d/1lHYRQKjqKCRXghUjwWkUB0HQ8ccKH6qa/view?usp=sharing) |<br> >> └──────`openvino-fp16`: | [Baidu Drive](https://pan.baidu.com/s/18p8HAyGJdmo2hham250b4A) | [Google Drive](https://drive.google.com/drive/folders/1s4KPSC4B0shG0INmQ6kZuPLnlUKAATyv?usp=sharing) |<br> > - [ ] `v5lite-g.pt`: | [Baidu Drive](https://pan.baidu.com/s/14zdTiTMI_9yTBgKGbv9pQw) | [Google Drive](https://drive.google.com/file/d/1oftzqOREGqDCerf7DtD5BZp9YWELlkMe/view?usp=sharing) |<br> Baidu Drive Password: `pogg`#### v5lite-s model: TFLite Float32, Float16, INT8, Dynamic range quantization, ONNX, TFJS, TensorRT, OpenVINO IR FP32/FP16, Myriad Inference Engin Blob, CoreML[https://github.com/PINTO0309/PINTO_model_zoo/tree/main/180_YOLOv5-Lite](https://github.com/PINTO0309/PINTO_model_zoo/tree/main/180_YOLOv5-Lite)#### Thanks for PINTO0309:[https://github.com/PINTO0309/PINTO_model_zoo/tree/main/180_YOLOv5-Lite](https://github.com/PINTO0309/PINTO_model_zoo/tree/main/180_YOLOv5-Lite)## Thanks for contributorsWe welcome your comments! We want to make contributing to YOLOv5-Lite as easy and transparent as possible. Thanks to a

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