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FabianHoerstFabianHoerst
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Fixing dependencies
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‎CellViT_Inference.ipynb

Lines changed: 76 additions & 75 deletions
Original file line numberDiff line numberDiff line change
@@ -1,54 +1,36 @@
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"gpuType": "T4",
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"authorship_tag": "ABX9TyNMQZ3sfZxtupkf49q2mk3U",
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"include_colab_link": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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"colab_type": "text",
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"id": "view-in-github"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/TIO-IKIM/CellViT-Inference/blob/main/CellViT_Inference.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "G0nASWl5KTeu"
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},
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"source": [
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"# CellViT Inference pipeline in Colab\n",
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"\n",
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"Here is an example ob how to install CellViT-Inference in Colab using some example slides. For runtime environment, please select a GPU runtime (e.g., T4 GPU)"
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],
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"metadata": {
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"id": "G0nASWl5KTeu"
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}
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "aRbdZBJCKmO-"
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},
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"source": [
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"## Setup/Installation\n",
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"\n",
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"As PyTorch is already installed, we can skip the torch installation commands"
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],
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"metadata": {
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"id": "aRbdZBJCKmO-"
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}
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]
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},
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{
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"cell_type": "code",
@@ -65,48 +47,53 @@
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},
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{
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"cell_type": "code",
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"source": [
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"!cellvit-check"
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],
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"execution_count": null,
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"metadata": {
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"id": "XVW6LP-mEBdZ"
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},
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"execution_count": null,
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"outputs": []
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"outputs": [],
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"source": [
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"!cellvit-check"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "sA3IYs8MKB3B"
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},
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"source": [
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"# Example for Inference\n",
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"\n",
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"Be careful: The free instances just provide 2 CPU cores for your runtime. Thus,we need to set the hardware limits accordingly and overwrite them"
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],
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"metadata": {
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"id": "sA3IYs8MKB3B"
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}
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"First, download the test database"
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],
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"metadata": {
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"id": "xnwQkbeqM8C_"
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}
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},
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"source": [
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"First, download the test database"
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]
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},
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{
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"cell_type": "code",
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"source": [
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"!cellvit-download-examples"
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],
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"execution_count": null,
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"metadata": {
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"id": "x-6SuMndM-mv"
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},
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"execution_count": null,
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"outputs": []
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"outputs": [],
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"source": [
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"!cellvit-download-examples"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "t4zMTE99MVKd"
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},
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"outputs": [],
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"source": [
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"!cellvit-inference \\\n",
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" --model HIPT \\\n",
@@ -119,24 +106,24 @@
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" --wsi_path ./test_database/BRACS/BRACS_1640_N_3_cropped.tiff \\\n",
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" --wsi_mpp 0.25 \\\n",
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" --wsi_magnification 40"
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],
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"metadata": {
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"id": "t4zMTE99MVKd"
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},
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"execution_count": null,
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"outputs": []
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"This also works for larger WSI"
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],
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"metadata": {
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"id": "YqYEwTC-MVeA"
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}
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},
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"source": [
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"This also works for larger WSI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "33_QyEyYFf9d"
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},
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"outputs": [],
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"source": [
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"!cellvit-inference \\\n",
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" --model HIPT \\\n",
@@ -146,30 +133,44 @@
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" --ray_remote_cpus 1 \\\n",
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" process_wsi \\\n",
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" --wsi_path ./test_database/x40_svs/JP2K-33003-2.svs"
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],
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"metadata": {
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"id": "33_QyEyYFf9d"
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},
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"execution_count": null,
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"outputs": []
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"The results can be found in the test_results folder"
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],
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"metadata": {
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"id": "0scuMhU_NmdC"
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}
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},
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"source": [
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"The results can be found in the test_results folder"
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]
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}
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],
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"authorship_tag": "ABX9TyNMQZ3sfZxtupkf49q2mk3U",
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"gpuType": "T4",
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"include_colab_link": true,
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"provenance": []
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},
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{
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"cell_type": "code",
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"source": [],
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"metadata": {
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"id": "0S6iMprONplW"
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"kernelspec": {
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"display_name": "cellvit-visualization",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"execution_count": null,
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"outputs": []
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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]
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

‎cellvit/inference/inference.py

Lines changed: 17 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -667,12 +667,18 @@ def process_wsi(
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filter_patches (bool, optional): Filter patches after processing. Defaults to False.
668668
"""
669669
wsi_path = Path(wsi_path)
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self.logger.info(f"Processing WSI: {wsi_path.name}")
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if wsi_path.suffix == ".dcm":
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self.logger.info(f"Processing WSI: {wsi_path.parent.name}")
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else:
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self.logger.info(f"Processing WSI: {wsi_path.name}")
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self.logger.info(f"Preparing WSI - Loading tissue region and prepare patches")
672675

673676
# create output directory
674677
self.outdir.mkdir(exist_ok=True, parents=True)
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wsi_outdir = self.outdir / wsi_path.stem
678+
if wsi_path.suffix == ".dcm":
679+
wsi_outdir = self.outdir / wsi_path.parent.name
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else:
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wsi_outdir = self.outdir / wsi_path.parent.stem
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wsi_outdir.mkdir(exist_ok=True, parents=True)
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# load metadata
@@ -899,7 +905,10 @@ def process_wsi(
899905
)
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901907
# saving/storing
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output_wsi_name = wsi_path.name.split(".")[0]
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if wsi_path.suffix == ".dcm":
909+
output_wsi_name = wsi_path.parent.name
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else:
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output_wsi_name = wsi_path.stem
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cell_dict_wsi = {
904913
"wsi_metadata": wsi.metadata,
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"type_map": self.label_map,
@@ -987,7 +996,11 @@ def process_wsi(
987996
if (self.outdir / "processed_files.json").exists():
988997
with open(self.outdir / "processed_files.json", "r") as infile:
989998
processed_files = ujson.load(infile)
990-
processed_files.append(wsi_path.name)
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1000+
if wsi_path.suffix == ".dcm":
1001+
processed_files.append(wsi_path.parent.name)
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else:
1003+
processed_files.append(wsi_path.name)
9911004
processed_files = list(set(processed_files))
9921005
with open(self.outdir / "processed_files.json", "w") as outfile:
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ujson.dump(processed_files, outfile)

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