Merge pull request #37 from Leengit/select_tiles

Version 2.0.0

example/tensorflow_stream.ipynb

@@ -0,0 +1,173 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "25408cb3-b6d6-4244-9346-6f3b3166cdb6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# install histomics_stream\n",
+    "!pip install -e /tf/notebooks/histomics_stream\n",
+    "\n",
+    "# add to system path\n",
+    "import sys\n",
+    "\n",
+    "sys.path.append(\"/tf/notebooks/histomics_stream/\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1ecc019-0935-4d07-a245-f61ca1836675",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import copy\n",
+    "import histomics_stream as hs\n",
+    "\n",
+    "# import tensorflow as tf\n",
+    "\n",
+    "print(\"Configuring with histomics_stream\")\n",
+    "\n",
+    "# Create a study and insert study-wide information\n",
+    "my_study0 = {\"version\": \"version-1\"}\n",
+    "my_study0[\"number_pixel_rows_for_tile\"] = 256\n",
+    "my_study0[\"number_pixel_columns_for_tile\"] = 256\n",
+    "my_slides = my_study0[\"slides\"] = {}\n",
+    "\n",
+    "# Add a slide to the study, including slide-wide information with it.\n",
+    "my_slide0 = my_slides[\"Slide_0\"] = {}\n",
+    "my_slide0[\"filename\"] = \"/tf/notebooks/histomics_stream/example/TCGA-BH-A0BZ-01Z-00-DX1.45EB3E93-A871-49C6-9EAE-90D98AE01913.svs\"\n",
+    "my_slide0[\"slide_name\"] = \"TCGA-BH-A0BZ-01Z-00-DX1\"\n",
+    "my_slide0[\"slide_group\"] = \"TCGA-BH-A0BZ\"\n",
+    "my_slide0[\"number_pixel_rows_for_chunk\"] = 2048\n",
+    "my_slide0[\"number_pixel_columns_for_chunk\"] = 2048\n",
+    "\n",
+    "# For each slide, find the appropriate resolution given the desired_magnification and\n",
+    "# magnification_tolerance.  In this example, we use the same parameters for each slide,\n",
+    "# but this is not required generally.\n",
+    "find_resolution_for_slide = hs.configure.FindResolutionForSlide(\n",
+    "    my_study0, desired_magnification=20, magnification_tolerance=0.02\n",
+    ")\n",
+    "for slide in my_study0[\"slides\"].values():\n",
+    "    find_resolution_for_slide(slide)\n",
+    "print(\"================================================================\")\n",
+    "print(f\"my_study0 = {my_study0}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "af6100da-943c-4e56-bf6d-d711169daedb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# We are going to demonstrate several approaches to choosing tiles.  Each approach will\n",
+    "# start with its own copy of the my_study0 that we have built so far.\n",
+    "\n",
+    "# Demonstrate TilesByGridAndMask without a mask\n",
+    "my_study_tiles_by_grid = copy.deepcopy(my_study0)\n",
+    "tiles_by_grid = hs.configure.TilesByGridAndMask(\n",
+    "    my_study_tiles_by_grid,\n",
+    "    number_pixel_overlap_rows_for_tile=32,\n",
+    "    number_pixel_overlap_columns_for_tile=32,\n",
+    "    randomly_select=100,\n",
+    ")\n",
+    "# We could apply this to a subset of the slides, but we will apply it to all slides in\n",
+    "# this example.\n",
+    "for slide in my_study_tiles_by_grid[\"slides\"].values():\n",
+    "    tiles_by_grid(slide)\n",
+    "print(\"================================================================\")\n",
+    "print(\"Finished with TilesByGrid\")\n",
+    "print(f\"my_study_tiles_by_grid = {my_study_tiles_by_grid}\")\n",
+    "\n",
+    "# Demonstrate TilesByGridAndMask with a mask\n",
+    "my_study_tiles_by_grid_and_mask = copy.deepcopy(my_study0)\n",
+    "tiles_by_grid_and_mask = hs.configure.TilesByGridAndMask(\n",
+    "    my_study_tiles_by_grid_and_mask,\n",
+    "    number_pixel_overlap_rows_for_tile=0,\n",
+    "    number_pixel_overlap_columns_for_tile=0,\n",
+    "    mask_filename=\"/tf/notebooks/histomics_stream/example/TCGA-BH-A0BZ-01Z-00-DX1.45EB3E93-A871-49C6-9EAE-90D98AE01913-mask.png\",\n",
+    "    randomly_select=100,\n",
+    ")\n",
+    "# We could apply this to a subset of the slides, but we will apply it to all slides in\n",
+    "# this example.\n",
+    "for slide in my_study_tiles_by_grid_and_mask[\"slides\"].values():\n",
+    "    tiles_by_grid_and_mask(slide)\n",
+    "print(\"================================================================\")\n",
+    "print(\"Finished with TilesByGridAndMask\")\n",
+    "print(f\"my_study_tiles_by_grid_and_mask = {my_study_tiles_by_grid_and_mask}\")\n",
+    "\n",
+    "# Demonstrate TilesByList\n",
+    "my_study_tiles_by_list = copy.deepcopy(my_study0)\n",
+    "tiles_by_list = hs.configure.TilesByList(\n",
+    "    my_study_tiles_by_list,\n",
+    "    randomly_select=5,\n",
+    "    tiles_dictionary=my_study_tiles_by_grid[\"slides\"][\"Slide_0\"][\"tiles\"],\n",
+    ")\n",
+    "# We could apply this to a subset of the slides, but we will apply it to all slides in\n",
+    "# this example.\n",
+    "for slide in my_study_tiles_by_list[\"slides\"].values():\n",
+    "    tiles_by_list(slide)\n",
+    "print(\"================================================================\")\n",
+    "print(\"Finished with TilesByList\")\n",
+    "print(f\"my_study_tiles_by_list = {my_study_tiles_by_list}\")\n",
+    "\n",
+    "# Demonstrate TilesRandomly\n",
+    "my_study_tiles_randomly = copy.deepcopy(my_study0)\n",
+    "tiles_randomly = hs.configure.TilesRandomly(my_study_tiles_randomly, randomly_select=3)\n",
+    "# We could apply this to a subset of the slides, but we will apply it to all slides in\n",
+    "# this example.\n",
+    "for slide in my_study_tiles_randomly[\"slides\"].values():\n",
+    "    tiles_randomly(slide)\n",
+    "print(\"================================================================\")\n",
+    "print(\"Finished with TilesRandomly\")\n",
+    "print(f\"my_study_tiles_randomly = {my_study_tiles_randomly}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "238948be-b2aa-4558-9c1a-d7dbd7b42cea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# We choose one of the above examples for further processing.\n",
+    "my_study_of_tiles = my_study_tiles_by_grid\n",
+    "\n",
+    "print(\"Creating a tensorflow Dataset with histomics_stream\")\n",
+    "\n",
+    "create_tensorflow_dataset = hs.tensorflow.CreateTensorFlowDataset()\n",
+    "tiles = create_tensorflow_dataset(my_study_of_tiles)\n",
+    "print(\"Finished with CreateTensorFlowDataset\")\n",
+    "\n",
+    "print(\"================================================================\")\n",
+    "print(tiles)\n",
+    "# print(\"================================================================\")\n",
+    "# tf.print(tiles)"
+   ]
+  }
+ ],
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