multiple updates

LungCoordinatesValidation/Untitled.ipynb

@@ -1,6 +1,20 @@
 {
- "cells": [],
- "metadata": {},
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# TODO: implement!"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }

LungDetectionTraining/filtering_luna_data.ipynb

@@ -0,0 +1,180 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Code used to extract only LUNA16 data from mixed dataset .json "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "from tqdm import tqdm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### train/val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 488/488 [00:00<00:00, 1172962.95it/s]\n",
+      "100%|██████████| 122/122 [00:00<00:00, 571099.43it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "384\n",
+      "96\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_list_file_path = f'/data/output/mixed_data/mixed_train_val0.json'\n",
+    "f = open(data_list_file_path)\n",
+    "data = json.load(f)\n",
+    "\n",
+    "train_luna = []\n",
+    "val_luna = []\n",
+    "for content in tqdm(data['training']):\n",
+    "    if 'LUNA16' in content['image']:\n",
+    "        train_luna.append({\n",
+    "            \"box\": content['box'],\n",
+    "            \"image\": content['image'],\n",
+    "            \"label\": content['label']\n",
+    "        })\n",
+    "\n",
+    "for content in tqdm(data['validation']):\n",
+    "    if 'LUNA16' in content['image']:\n",
+    "        val_luna.append({\n",
+    "            \"box\": content['box'],\n",
+    "            \"image\": content['image'],\n",
+    "            \"label\": content['label']\n",
+    "        })\n",
+    "\n",
+    "print(len(train_luna))\n",
+    "print(len(val_luna))\n",
+    "\n",
+    "value = {\n",
+    "    \"training\": train_luna,\n",
+    "    \"validation\": val_luna\n",
+    "}\n",
+    "\n",
+    "save_file = open(\n",
+    "    '/data/output/unique_data/luna_train_val.json',\n",
+    "    'w'\n",
+    ")\n",
+    "json.dump(value, save_file, indent=5)\n",
+    "save_file.close()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 155/155 [00:00<00:00, 773948.95it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "121\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_list_file_path = f'/data/output/mixed_data/mixed_test.json'\n",
+    "f = open(data_list_file_path)\n",
+    "data = json.load(f)\n",
+    "\n",
+    "test_luna = []\n",
+    "val_luna = []\n",
+    "for content in tqdm(data['test']):\n",
+    "    if 'LUNA16' in content['image']:\n",
+    "        test_luna.append({\n",
+    "            \"box\": content['box'],\n",
+    "            \"image\": content['image'],\n",
+    "            \"label\": content['label']\n",
+    "        })\n",
+    "\n",
+    "print(len(test_luna))\n",
+    "\n",
+    "value = {\n",
+    "    \"test\": test_luna\n",
+    "}\n",
+    "\n",
+    "save_file = open(\n",
+    "    '/data/output/unique_data/luna_test.json',\n",
+    "    'w'\n",
+    ")\n",
+    "json.dump(value, save_file, indent=5)\n",
+    "save_file.close()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

LungDetectionTraining/generate_transforms.py

@@ -16,12 +16,11 @@
 )
 from monai.apps.detection.transforms.dictionary import (
     AffineBoxToImageCoordinated,
-    AffineBoxToWorldCoordinated,
     BoxToMaskd,
     ClipBoxToImaged,
     ConvertBoxToStandardModed,
     MaskToBoxd,
-    RandCropBoxByPosNegLabeld,
+    RandCropBoxByPosNegLabeld, # RandCropByPosNegLabeld
     RandFlipBoxd,
     RandRotateBox90d,
     RandZoomBoxd,