From bdac2263a51bac856774ff5ec57c443ef6c88a24 Mon Sep 17 00:00:00 2001 From: Tater Totterson Date: Sat, 27 Sep 2025 15:04:16 -0500 Subject: [PATCH] Update README.md --- README.md | 90 ++++++++++++++++++++++++++++++------------------------- 1 file changed, 50 insertions(+), 40 deletions(-) diff --git a/README.md b/README.md index acf28f0..b85f92d 100644 --- a/README.md +++ b/README.md @@ -3,76 +3,86 @@

microWakeWord Trainer Docker

-Easily train microWakeWord detection models with this pre-built Docker image. +# 🥔 MicroWakeWord Trainer – Tater Approved -## Quick Start +**✅ Tater Totterson tested & working on an NVIDIA RTX 3070 Laptop GPU (8 GB VRAM).** +Easily train microWakeWord detection models with this pre-built Docker image and JupyterLab notebook. -Follow these steps to get started with the microWakeWord Trainer: +--- -### 1. Pull the Pre-Built Docker Image +## 🚀 Quick Start + +Follow these steps to get up and running: + +### 1️⃣ Pull the Pre-Built Docker Image -Pull the Docker image from Docker Hub: ```bash docker pull ghcr.io/tatertotterson/microwakeword:latest ``` -### 2. Run the Docker Container +--- + +### 2️⃣ Run the Docker Container -Start the container with a mapped volume for saving your data and expose the Jupyter Notebook: ```bash docker run --rm -it \ - --gpus all \ + --gpus all \ -p 8888:8888 \ -v $(pwd):/data \ ghcr.io/tatertotterson/microwakeword:latest ``` ---gpus all: Enables GPU acceleration. --p 8888:8888: Exposes the Jupyter Notebook on port 8888. --v $(pwd):/data: Maps the current directory to the container's /data directory for saving your files. -### 3. Access Jupyter Notebook +**What these flags do:** +- `--gpus all` → Enables GPU acceleration +- `-p 8888:8888` → Exposes JupyterLab on port 8888 +- `-v $(pwd):/data` → Saves your work in the current folder + +--- + +### 3️⃣ Open JupyterLab + +Visit [http://localhost:8888](http://localhost:8888) in your browser — the notebook UI will open. + +--- + +### 4️⃣ Set Your Wake Word + +At the **top of the notebook**, find this line: -Open your web browser and navigate to: ```bash -http://localhost:8888 +TARGET_WORD = "hey_tater" # Change this to your desired wake word ``` -The notebook interface should appear. -### 4. Edit the Wake Word +Change `"hey_tater"` to your desired wake word (phonetic spellings often work best). -Locate and edit the second cell in the notebook to specify your desired wake word: -```bash -target_word = 'khum_puter' # Phonetic spellings may produce better samples -``` -Change 'khum_puter' to your desired wake word. +--- -### 5. Run the Notebook -Run all cells in the notebook. The process will: +### 5️⃣ Run the Notebook -Generate wake word samples. -Train a detection model. -Output a quantized .tflite model for on-device use. +Run all cells in the notebook. This process will: +- Generate wake word samples +- Train a detection model +- Output a quantized `.tflite` model ready for on-device use -### 6. Retrieve the Trained Model and JSON -Once the training is complete, the quantized .tflite model and .json will be available for download. Follow the instructions in the last cell of the notebook to download the model. +--- -## Resetting to a Clean State -If you need to start fresh: +### 6️⃣ Retrieve the Trained Model & JSON -### Delete your data folder: -Locate and delete the data folder that was mapped to your Docker container. +When training finishes, download links for both the `.tflite` model and its `.json` manifest will be displayed in the last cell. -### Restart the Docker container: -Run the container again using the steps provided above. +--- -### Fresh notebook generated: -Upon restarting, a clean version of the training notebook will be placed in the newly created data directory. -This will reset your MicroWakeWord-Training-Docker environment to its initial state. +## 🔄 Resetting to a Clean State -## Credits - -This project builds upon the excellent work of [kahrendt/microWakeWord](https://github.com/kahrendt/microWakeWord). A huge thank you to the original authors for their contributions to the open-source community! +If you need to start fresh: +1. Delete the `data` folder that was mapped to your Docker container. +2. Restart the container using the steps above. +3. A fresh copy of the notebook will be placed into the `data` directory. +--- +## 🙌 Credits +This project builds upon the excellent work of [kahrendt/microWakeWord](https://github.com/kahrendt/microWakeWord). +Huge thanks to the original authors for their contributions to the open-source community!