Bird classification model (in progress)

CosmicBee · March 18, 2024, 2:18am

Hi there,

I’ve been working on a bird classification model. I’m hoping to get it onto my TinyML hardware but the RAM requirements are currently too large as I used a rather large input size. I’m working to further adjust it but I am fairly new to machine learning so it’s a process.

github.com

Timo614/machine-learning/blob/main/birds-tflite-test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dbe229d0-ebc1-48b6-a501-fb2063607363",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib import Path\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "code",

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I’m not sure if there are any downsides to my approach as my model is fairly small for the given number of outputs. I’m still adjusting it and I lost some accuracy with it early on before I refined my methods.

I included the heatmap and f1 scores from my model.

Apologies for the cross post from the discord show and tell just figured this is a larger community in retrospect (I can delete the discord message in that channel if needed from last week).

Thanks,

Tim

CosmicBee · March 26, 2024, 1:40pm

I refined my techniques (and came up with a few new ones) and ended up with an 85% accuracy model with int8 quantization at 96x96.

Fairly happy with the results as it appears it will fit on my microcontroller.

github.com

Timo614/machine-learning/blob/main/birds-tflite-test-96-96-84.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dbe229d0-ebc1-48b6-a501-fb2063607363",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from pathlib import Path\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,

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