{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "weights = \"imagenet\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_keras_to_tfjs(model, filename):\n",
    "    model.save(filename + \".h5\")\n",
    "    import os\n",
    "    os.mkdir(filename)\n",
    "    os.system(\"tensorflowjs_converter --input_format keras ./{}.h5 ./{}\".format(filename, filename))\n",
    "    os.system(\"rm {}.h5\".format(filename))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Densenet201"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/densenet/densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
      "74836368/74836368 [==============================] - 5s 0us/step\n",
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/teosanchez/anaconda3/lib/python3.11/site-packages/keras/src/engine/training.py:3079: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n",
      "  saving_api.save_model(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    }
   ],
   "source": [
    "pooling  = [\"avg\", \"max\"]\n",
    "for pool in pooling:\n",
    "    model = tf.keras.applications.DenseNet201(include_top = False, weights = weights, pooling = pool)\n",
    "    filename = \"densenet201_pooling={1}\".format(weights, pool)\n",
    "    convert_keras_to_tfjs(model, filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Densenet169"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n",
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    }
   ],
   "source": [
    "pooling  = [\"avg\", \"max\"]\n",
    "for pool in pooling:\n",
    "    model = tf.keras.applications.DenseNet169(include_top = False, weights = weights, pooling = pool)\n",
    "    filename = \"densenet169_pooling={1}\".format(weights, pool)\n",
    "    convert_keras_to_tfjs(model, filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Resnet152"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet152_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
      "234698864/234698864 [==============================] - 10s 0us/step\n",
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/teosanchez/anaconda3/lib/python3.11/site-packages/keras/src/engine/training.py:3079: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n",
      "  saving_api.save_model(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    }
   ],
   "source": [
    "pooling  = [\"avg\", \"max\"]\n",
    "for pool in pooling:\n",
    "    model = tf.keras.applications.ResNet152(include_top = False, weights = weights, pooling = pool)\n",
    "    filename = \"resnet152_pooling={1}\".format(weights, pool)\n",
    "    convert_keras_to_tfjs(model, filename)"
   ]
  }
 ],
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