add better contour plot using argmin and abs

.gitattributes

@@ -28,3 +28,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.ckpt filter=lfs diff=lfs merge=lfs -text
 data/**/*.json filter=lfs diff=lfs merge=lfs -text
 data/**/*.csv filter=lfs diff=lfs merge=lfs -text
+*.ipynb filter=lfs diff=lfs merge=lfs -text

notebooks/1.0-hfk-datamodules-exploration.ipynb

@@ -1,204 +1,3 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Exploring Code for Data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "metadata = pd.read_csv(\"../data/focus/metadata.csv\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "metadata"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "idx = 0\n",
-    "# File Path\n",
-    "metadata.iloc[idx, 1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Focus Value\n",
-    "metadata.iloc[idx, 5]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Testing FocusDataSet"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from importlib.machinery import SourceFileLoader\n",
-    "\n",
-    "focus_datamodule = SourceFileLoader(\"focus_datamodule\", \"../src/datamodules/focus_datamodule.py\").load_module()\n",
-    "from focus_datamodule import FocusDataSet\n",
-    "\n",
-    "ds = FocusDataSet(\"../data/focus/metadata.csv\", \"../data/focus/\")\n",
-    "\n",
-    "for d in ds:\n",
-    "    break\n",
-    "\n",
-    "d"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from focus_datamodule import FocusDataModule\n",
-    "\n",
-    "datamodule = FocusDataModule(data_dir=\"../data/focus\", csv_file=\"../data/focus/metadata.csv\")\n",
-    "datamodule.setup()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "for data in datamodule.test_dataloader():\n",
-    "    break\n",
-    "\n",
-    "len(data[\"focus_value\"])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import types\n",
-    "import importlib.machinery\n",
-    "focus_module = SourceFileLoader('focus_module', '../src/models/focus_module.py').load_module()\n",
-    "from focus_module import FocusLitModule\n",
-    "\n",
-    "model = FocusLitModule()\n",
-    "\n",
-    "model.step(data)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Benchmark in-memory and from disk"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import time\n",
-    "\n",
-    "iterations = 10"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "datamodule = FocusDataModule(data_dir=\"../data/focus150\", csv_file=\"../data/focus150/metadata.csv\")\n",
-    "datamodule.setup()\n",
-    "\n",
-    "\n",
-    "start = time.perf_counter()\n",
-    "counter = 0\n",
-    "for i in range(iterations):\n",
-    "    for data in datamodule.train_dataloader():\n",
-    "        counter += 1\n",
-    "\n",
-    "print(time.perf_counter() - start)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "datamodule = FocusDataModule(data_dir=\"../data/focus150\", csv_file=\"../data/focus150/metadata.csv\", in_memory=False)\n",
-    "datamodule.setup()\n",
-    "\n",
-    "start = time.perf_counter()\n",
-    "counter = 0\n",
-    "for i in range(iterations):\n",
-    "    for data in datamodule.train_dataloader():\n",
-    "        counter += 1\n",
-    "print(time.perf_counter() - start)"
-   ]
-  }
- ],
- "metadata": {
-  "interpreter": {
-   "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac"
-  },
-  "kernelspec": {
-   "display_name": "Python 3.9.7 64-bit",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb54303b39da6232abd0c39c72d4133d38f26cf103c39ec5a2fc4f100e475c9a
+size 4381

notebooks/2.0-hfk-convolutional_testing.ipynb

@@ -1,203 +1,3 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Testing FocusDataSet"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2450\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "{'image': array([[[211, 185,  62],\n",
-       "         [216, 192,  68],\n",
-       "         [223, 198,  79],\n",
-       "         ...,\n",
-       "         [214, 190,  64],\n",
-       "         [222, 199,  71],\n",
-       "         [224, 201,  73]],\n",
-       " \n",
-       "        [[218, 192,  69],\n",
-       "         [223, 197,  74],\n",
-       "         [229, 205,  83],\n",
-       "         ...,\n",
-       "         [216, 193,  65],\n",
-       "         [225, 202,  74],\n",
-       "         [226, 203,  75]],\n",
-       " \n",
-       "        [[223, 198,  72],\n",
-       "         [228, 202,  79],\n",
-       "         [234, 210,  88],\n",
-       "         ...,\n",
-       "         [220, 197,  69],\n",
-       "         [228, 205,  77],\n",
-       "         [226, 203,  73]],\n",
-       " \n",
-       "        ...,\n",
-       " \n",
-       "        [[157, 138,  17],\n",
-       "         [163, 145,  21],\n",
-       "         [178, 157,  32],\n",
-       "         ...,\n",
-       "         [166, 169,  40],\n",
-       "         [170, 173,  42],\n",
-       "         [176, 179,  46]],\n",
-       " \n",
-       "        [[145, 126,   5],\n",
-       "         [155, 137,  13],\n",
-       "         [177, 156,  31],\n",
-       "         ...,\n",
-       "         [156, 158,  31],\n",
-       "         [166, 169,  40],\n",
-       "         [175, 178,  47]],\n",
-       " \n",
-       "        [[147, 128,   7],\n",
-       "         [159, 141,  17],\n",
-       "         [181, 160,  35],\n",
-       "         ...,\n",
-       "         [149, 151,  24],\n",
-       "         [162, 164,  37],\n",
-       "         [172, 175,  46]]], dtype=uint8),\n",
-       " 'focus_value': tensor(0.5450)}"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from importlib.machinery import SourceFileLoader\n",
-    "\n",
-    "focus_datamodule = SourceFileLoader(\"focus_datamodule\", \"../src/datamodules/focus_datamodule.py\").load_module()\n",
-    "from focus_datamodule import FocusDataSet\n",
-    "\n",
-    "ds = FocusDataSet(\"../data/focus150/metadata.csv\", \"../data/focus150/\")\n",
-    "\n",
-    "counter = 0\n",
-    "for d in ds:\n",
-    "    counter += 1\n",
-    "\n",
-    "print(counter)\n",
-    "\n",
-    "d"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 81,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "14\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "torch.Size([64, 1])"
-      ]
-     },
-     "execution_count": 81,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from focus_datamodule import FocusDataModule\n",
-    "\n",
-    "datamodule = FocusDataModule(data_dir=\"../data/focus150\", csv_file=\"../data/focus150/metadata.csv\")\n",
-    "datamodule.setup()\n",
-    "\n",
-    "for data in datamodule.test_dataloader():\n",
-    "    break\n",
-    "\n",
-    "len(data[\"focus_value\"])\n",
-    "\n",
-    "# https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html\n",
-    "import torch\n",
-    "import torch.nn as nn\n",
-    "import torch.nn.functional as F\n",
-    "\n",
-    "class Net(nn.Module):\n",
-    "    def __init__(self):\n",
-    "        super().__init__()\n",
-    "        pool_size = 3\n",
-    "        \n",
-    "        conv1_size = 5\n",
-    "        conv1_out = 6\n",
-    "        conv2_size = 5\n",
-    "        conv2_out = 16\n",
-    "        size_img = 150\n",
-    "\n",
-    "        size_img -= conv1_size - 1\n",
-    "        size_img = int( (size_img) / pool_size)\n",
-    "        size_img -= conv2_size - 1\n",
-    "        size_img = int(size_img / pool_size)\n",
-    "\n",
-    "        print(size_img)\n",
-    "\n",
-    "        self.model = nn.Sequential(\n",
-    "            nn.Conv2d(3, conv1_out, conv1_size),\n",
-    "            nn.MaxPool2d(pool_size, pool_size),\n",
-    "            nn.Conv2d(conv1_out, conv2_out, conv2_size),\n",
-    "            nn.MaxPool2d(pool_size, pool_size),\n",
-    "            nn.Flatten(),\n",
-    "            nn.Linear(conv2_out * size_img * size_img, 120), # 16 * 34 * 34 or [64, 16, 15, 15]\n",
-    "            nn.Linear(120, 84),\n",
-    "            nn.Linear(84, 1)\n",
-    "        )\n",
-    "\n",
-    "    def forward(self, x):\n",
-    "        x = self.model(x)\n",
-    "        return x\n",
-    "\n",
-    "\n",
-    "net = Net()\n",
-    "\n",
-    "net(data[\"image\"]).shape"
-   ]
-  }
- ],
- "metadata": {
-  "interpreter": {
-   "hash": "f9f85f796d01129d0dd105a088854619f454435301f6ffec2fea96ecbd9be4ac"
-  },
-  "kernelspec": {
-   "display_name": "Python 3.9.7 64-bit",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
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+oid sha256:f546606a42c83af81a425f6d05cb0fafa0522a373be7c6b9a85d166387dc49b4
+size 5434