From f4434fd2e2ab6158050ca6970b6f5405901c55e6 Mon Sep 17 00:00:00 2001 From: Bharath Sudharsan Date: Sat, 23 Jul 2022 11:00:24 +0100 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b60143b..b48814a 100644 --- a/README.md +++ b/README.md @@ -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.