taco/microWakeWord-Trainer-Nvidia-Docker
1
0
Fork 0
mirror of https://github.com/TaterTotterson/microWakeWord-Trainer-Nvidia-Docker.git synced 2026-06-12 20:10:19 -06:00
Code Issues Packages Projects Releases Wiki Activity

Update advanced_training_notebook.ipynb

Browse Source
This commit is contained in:
MasterPhooey
2025-01-05 08:24:04 -06:00
committed by GitHub
parent 365c0eb195
commit 571ed1ddfc
1 changed files with 39 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files

59
advanced_training_notebook.ipynb
View File

@@ -10,7 +10,6 @@
" <img src=\"https://raw.githubusercontent.com/MasterPhooey/MicroWakeWord-Trainer-Docker/refs/heads/main/mmw.png\" alt=\"MicroWakeWord Trainer Logo\" width=\"100\" />\n",
" <h1>MicroWakeWord Trainer Docker</h1>\n",
"</div>\n",
"**This notebook requires 24G of Vram.**\n",
"\n",
"This notebook steps you through training a robust microWakeWord model. It is intended as a **starting point** for users looking to create a high-performance wake word detection model. This notebook is optimized for Python 3.10.\n",
"\n",
@@ -641,7 +640,7 @@
"config[\"clip_duration_ms\"] = 2000 # Increased\n",
"\n",
"config[\"target_minimization\"] = 0.9\n",
"config[\"minimization_metric\"] = None # Updated\n",
"config[\"minimization_metric\"] = \"false_positive_rate\" # Updated\n",
"config[\"maximization_metric\"] = \"average_viable_recall\"\n",
"\n",
"with open(os.path.join(\"training_parameters.yaml\"), \"w\") as file:\n",
@@ -676,20 +675,20 @@
"--training_config='training_parameters.yaml' \\\n",
"--train 1 \\\n",
"--restore_checkpoint 1 \\\n",
"--test_tf_nonstreaming 1 \\\n",
"--test_tflite_nonstreaming 1 \\\n",
"--test_tflite_nonstreaming_quantized 1 \\\n",
"--test_tflite_streaming 1 \\\n",
"--test_tf_nonstreaming 0 \\\n",
"--test_tflite_nonstreaming 0 \\\n",
"--test_tflite_nonstreaming_quantized 0 \\\n",
"--test_tflite_streaming 0 \\\n",
"--test_tflite_streaming_quantized 1 \\\n",
"--use_weights \"best_weights\" \\\n",
"mixednet \\\n",
"--pointwise_filters \"64,96,128,160\" \\\n",
"--repeat_in_block \"2,2,3,3\" \\\n",
"--mixconv_kernel_sizes '[5], [7,11], [9,15], [17,23]' \\\n",
"--residual_connection \"1,1,1,0\" \\\n",
"--first_conv_filters 48 \\\n",
"--first_conv_kernel_size 7 \\\n",
"--stride 2 \n"
"--pointwise_filters \"64,64,64,64\" \\\n",
"--repeat_in_block \"1,1,1,1\" \\\n",
"--mixconv_kernel_sizes '[5], [7,11], [9,15], [23]' \\\n",
"--residual_connection \"0,0,0,0\" \\\n",
"--first_conv_filters 32 \\\n",
"--first_conv_kernel_size 5 \\\n",
"--stride 2\n"
]
},
{
@@ -702,7 +701,9 @@
"source": [
"import shutil\n",
"import json\n",
"from IPython.display import FileLink, HTML\n",
"from http.server import HTTPServer, SimpleHTTPRequestHandler\n",
"import threading\n",
"from pathlib import Path\n",
"\n",
"# Copy the TFLite model file to the working directory\n",
"source_path = \"trained_models/wakeword/tflite_stream_state_internal_quant/stream_state_internal_quant.tflite\"\n",
@@ -712,7 +713,7 @@
"# Define the JSON metadata for the model\n",
"json_data = {\n",
" \"type\": \"micro\",\n",
" \"wake_word\": \"hey_norman\", # Adjust based on your target wake word\n",
" \"wake_word\": \"khum_puter\", # Adjust based on your target wake word\n",
" \"author\": \"master phooey\",\n",
" \"website\": \"https://github.com/MasterPhooey/MicroWakeWord-Trainer-Docker\",\n",
" \"model\": \"stream_state_internal_quant.tflite\",\n",
@@ -732,19 +733,37 @@
"with open(json_path, \"w\") as json_file:\n",
" json.dump(json_data, json_file, indent=2)\n",
"\n",
"# Generate download links with styled HTML\n",
"tflite_link = FileLink(destination_path)\n",
"json_link = FileLink(json_path)\n",
"# Custom HTTPRequestHandler to set the Content-Disposition header\n",
"class CustomHTTPRequestHandler(SimpleHTTPRequestHandler):\n",
" def end_headers(self):\n",
" if self.path.endswith(\".json\"):\n",
" self.send_header(\"Content-Disposition\", \"attachment\")\n",
" super().end_headers()\n",
"\n",
"# Start an HTTP server in a separate thread\n",
"def start_server():\n",
" server = HTTPServer((\"0.0.0.0\", 8000), CustomHTTPRequestHandler)\n",
" print(\"Serving files on http://localhost:8000\")\n",
" server.serve_forever()\n",
"\n",
"thread = threading.Thread(target=start_server, daemon=True)\n",
"thread.start()\n",
"\n",
"# Generate download links with styled HTML\n",
"html_content = f\"\"\"\n",
"<div align=\\\"center\\\">,\n",
"<img src=\\\"https://raw.githubusercontent.com/MasterPhooey/MicroWakeWord-Trainer-Docker/refs/heads/main/mmw.png\\\" alt=\\\"MicroWakeWord Trainer Logo\\\" width=\\\"100\\\" />\\n\"\n",
"<h1>MicroWakeWord Trainer Docker</h1>\n",
"</div>\\n\n",
"<h3 style=\"color:orange;\">Your files are ready for download:</h3>\n",
"<ul>\n",
" <li><b><a href=\"{tflite_link.url}\" target=\"_blank\" style=\"color:orange;\">TFLite Model: stream_state_internal_quant.tflite</a></b></li>\n",
" <li><b><a href=\"{json_link.url}\" target=\"_blank\" style=\"color:orange;\">JSON Metadata: stream_state_internal_quant.json</a></b></li>\n",
" <li><b><a href=\"http://localhost:8000/stream_state_internal_quant.tflite\" target=\"_blank\" style=\"color:orange;\">TFLite Model: stream_state_internal_quant.tflite</a></b></li>\n",
" <li><b><a href=\"http://localhost:8000/stream_state_internal_quant.json\" target=\"_blank\" style=\"color:orange;\">JSON Metadata: stream_state_internal_quant.json</a></b></li>\n",
"</ul>\n",
"<p style=\"font-size:12px; color:gray;\">Click the links to download the files. Ensure the files are moved to the correct directory for deployment.</p>\n",
"\"\"\"\n",
"\n",
"from IPython.display import HTML\n",
"display(HTML(html_content))"
]
}