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Update README.md

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Bharath Sudharsan 2022-07-23 11:00:24 +01:00
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@ -23,9 +23,9 @@ Following can be observed from the video:
- To collect images on a PC and train an ML classifier, install EverywhereML Python package.
- To test the TinyML-CAM pipeline, users only require an ESP32 of any variant:
- [AI Thinker](https://randomnerdtutorials.com/program-upload-code-esp32-cam/) (the most widely used)
- [Espressif](https://www.espressif.com/en/products/devkits/esp-eye/overview)
- [M5Stack](https://shop.m5stack.com/products/esp32-camera?variant=16804741316698) (recommend as it comes with 4 Mb external PSRAM)
- [Espressif](https://www.espressif.com/en/products/devkits/esp-eye/overview)
### Code
- [[ino]-CameraWebServer.ino](https://github.com/bharathsudharsan/TinyML-CAM/blob/main/%5Bino%5D-CameraWebServer.ino) - For image dataset collection. After upload to ESP32, it will connect to WiFi network and start an HTTP video streaming server that can be accessed from any web broswer.
- [[h]-HogClassifier.h](https://github.com/bharathsudharsan/TinyML-CAM/blob/main/%5Bh%5D-HogClassifier.h) - Contains the RandomForestClassifier trained using the collected image data.