manifest.imjoy.json

{
 "name": "ImJoy Repository",
 "description": "ImJoy plugin repository.",
 "uri_root": "",
 "version": "0.2.0",
 "plugins": [
  {
   "name": "3D-visualization",
   "type": "window",
   "tags": [],
   "ui": "Illustrate 3D visualization with vtk in the browser",
   "version": "0.1.0",
   "api_version": "0.1.2",
   "description": "Demonstration of 3D visualization wiht vtk.",
   "icon": "extension",
   "inputs": null,
   "outputs": null,
   "dependencies": [],
   "defaults": {
    "w": 30,
    "h": 20
   },
   "uri": "imjoy-plugins/3D-visualization.imjoy.html"
  },
  {
   "name": "CARE",
   "type": "native-python",
   "version": "0.1.20",
   "api_version": "0.1.2",
   "description": "This plugin demonstrates denoising using CARE.",
   "tags": [
    "Linux CPU",
    "Linux GPU",
    "Windows CPU",
    "Windows GPU",
    "MacOS CPU"
   ],
   "ui": "",
   "inputs": null,
   "outputs": null,
   "flags": [],
   "icon": null,
   "env": {
    "CPU": "conda create -n care-cpu python=3.6.7",
    "GPU": "conda create -n care-gpu python=3.6.7",
    "macOS CPU": "conda create -n care-mac-cpu python=3.6.7"
   },
   "requirements": {
    "Linux CPU": [
     "pip: tensorflow==1.15.0 keras==2.1.5 Pillow csbdeep==0.4.1 tifffile six"
    ],
    "Linux GPU": [
     "pip: tensorflow-gpu==1.15.0 keras==2.1.5 Pillow csbdeep==0.4.1 tifffile six gputil"
    ],
    "Windows CPU": [
     "pip: tensorflow==1.15.0 keras==2.1.5 Pillow csbdeep==0.4.1 tifffile six"
    ],
    "Windows GPU": [
     "pip: tensorflow-gpu==1.15.0 keras==2.1.5 Pillow csbdeep==0.4.1 tifffile six gputil"
    ],
    "MacOS CPU": [
     "pip: tensorflow==1.5.0 keras==2.1.5 Pillow csbdeep==0.4.1 tifffile six"
    ]
   },
   "dependencies": [
    "oeway/ImJoy-Plugins:Im2Im-Dashboard",
    "oeway/ImJoy-Plugins:launchpad",
    "oeway/ImJoy-Plugins:Tabbed-Docs"
   ],
   "cover": [
    "https://oeway.github.io/ImJoy-Plugins/care/care-cover.gif"
   ],
   "uri": "imjoy-plugins/CARE.imjoy.html"
  },
  {
   "name": "DPNUnet",
   "type": "native-python",
   "version": "0.2.10",
   "description": "Nuclei segmentation with deep learning.",
   "tags": [
    "GPU"
   ],
   "ui": "",
   "cover": "https://imjoy-team.github.io/example-plugins/dpnunet/dpnunet-cover.png",
   "inputs": null,
   "outputs": null,
   "flags": [],
   "icon": "extension",
   "api_version": "0.1.5",
   "env": {
    "CPU": [
     "conda create -n dsb2018-cpu python=3.6.8"
    ],
    "GPU": [
     "conda create -n dsb2018-gpu python=3.6.8"
    ]
   },
   "requirements": {
    "CPU": [
     "pip: descartes palettable geojson read-roi gputil namedlist",
     "pip: lightgbm imgaug pandas imageio",
     "conda: opencv tqdm scipy=1.0.0",
     "conda: pytorch=0.4.1 torchvision==0.2.0 -c pytorch",
     "pip: tensorboardX",
     "repo: https://github.com/oeway/DPNUnet-Segmentation"
    ],
    "GPU": [
     "pip: descartes palettable geojson read-roi gputil namedlist",
     "pip: lightgbm imgaug pandas imageio",
     "conda: opencv tqdm scipy=1.0.0",
     "conda: pytorch=0.4.1 torchvision==0.2.0 cuda90 -c pytorch",
     "pip: tensorboardX",
     "repo: https://github.com/oeway/DPNUnet-Segmentation"
    ]
   },
   "dependencies": [
    "oeway/ImJoy-Plugins:Im2Im-Dashboard",
    "oeway/ImJoy-Plugins:ImageAnnotator",
    "oeway/ImJoy-Plugins:launchpad",
    "oeway/ImJoy-Plugins:Tabbed-Docs"
   ],
   "uri": "imjoy-plugins/DPNUnet.imjoy.html"
  },
  {
   "name": "DeepBindScan",
   "type": "native-python",
   "version": "0.2.15",
   "api_version": "0.1.3",
   "description": "Predict binding affinity of TF/RBP to a given DNA/RNA sequence.",
   "tags": [],
   "ui": "",
   "inputs": null,
   "outputs": null,
   "flags": [],
   "icon": "extension",
   "env": "conda create -n deepbindscan python=3.6.8",
   "requirements": [
    "conda: h5py bioconda::pybedtools bioconda::pyfaidx numpy pandas",
    "pip: -U tensorflow==1.15.0 keras==2.1.6 kipoi kipoiseq"
   ],
   "dependencies": [
    "imjoy-team/example-plugins:SchemaIO"
   ],
   "cmd": "KERAS_BACKEND=tensorflow python",
   "uri": "imjoy-plugins/DeepBindScan.imjoy.html"
  },
  {
   "name": "HPA-Classification",
   "type": "window",
   "tags": [],
   "ui": [
    {
     "model": {
      "id": "model",
      "type": "choose",
      "options": [
       "ShuffleNet-V2"
      ],
      "placeholder": "ShuffleNet-V2"
     }
    }
   ],
   "version": "0.1.23",
   "api_version": "0.1.2",
   "url": "",
   "description": "ShuffleNetV2 for HPA.",
   "icon": "extension",
   "inputs": null,
   "outputs": null,
   "env": null,
   "requirements": [
    "https://cdn.jsdelivr.net/npm/apexcharts",
    "https://cdn.jsdelivr.net/npm/@tensorflow/tfjs",
    "https://cdn.jsdelivr.net/npm/simpleheat@0.4.0/simpleheat.min.js",
    "https://cdn.jsdelivr.net/gh/photopea/UTIF.js@4f1b10cb09e244cfd4f9631245d2231537148be7/UTIF.js"
   ],
   "dependencies": [
    "https://github.com/raw/imjoy-team/example-plugins/master/imjoy-plugins/HPA-Image-Selection.imjoy.html"
   ],
   "defaults": {
    "w": 60,
    "h": 20,
    "standalone": true
   },
   "cover": "https://imjoy-team.github.io/example-plugins/hpa-classification/hpa-classification-cover.gif",
   "uri": "imjoy-plugins/HPA-Classification.imjoy.html"
  },
  {
   "name": "HPA-Image-Selection",
   "type": "window",
   "tags": [],
   "ui": "",
   "version": "0.1.4",
   "api_version": "0.1.2",
   "description": "This is a backbone plugin for using Vue.js in ImJoy",
   "icon": "extension",
   "inputs": null,
   "outputs": null,
   "env": "",
   "requirements": [
    "https://cdnjs.cloudflare.com/ajax/libs/vue/2.5.22/vue.min.js"
   ],
   "dependencies": [],
   "defaults": {
    "w": 50,
    "h": 30
   },
   "runnable": true,
   "uri": "imjoy-plugins/HPA-Image-Selection.imjoy.html"
  },
  {
   "name": "HPA-UMAP",
   "type": "window",
   "tags": [],
   "ui": "Explore protein localization patterns in HPA images.",
   "version": "0.3.11",
   "api_version": "0.1.2",
   "description": "Explore protein localization patterns in HPA images.",
   "icon": "photo",
   "inputs": null,
   "outputs": null,
   "requirements": [
    "https://cdn.plot.ly/plotly-latest.min.js",
    "https://unpkg.com/papaparse@latest/papaparse.min.js",
    "https://cdn.jsdelivr.net/npm/vue@2.6.10/dist/vue.min.js",
    "https://unpkg.com/spectre.css/dist/spectre.min.css",
    "https://unpkg.com/spectre.css/dist/spectre-exp.min.css",
    "https://unpkg.com/spectre.css/dist/spectre-icons.min.css"
   ],
   "dependencies": [],
   "defaults": {
    "w": 50,
    "h": 20,
    "fullscreen": true
   },
   "cover": "https://oeway.github.io/ImJoy-Plugins/hpa-umap/hpa-umap-cover.gif",
   "uri": "imjoy-plugins/HPA-UMAP.imjoy.html"
  },
  {
   "name": "ImageAnnotator",
   "type": "window",
   "tags": [],
   "ui": "",
   "version": "0.5.76",
   "api_version": "0.1.5",
   "description": "An image annotator made with OpenLayers",
   "icon": "extension",
   "inputs": null,
   "outputs": null,
   "env": "",
   "requirements": [
    "https://cdn.jsdelivr.net/npm/vue@2.6.10/dist/vue.min.js",
    "https://cdn.jsdelivr.net/npm/openlayers@4.6.5/css/ol.css",
    "https://cdn.jsdelivr.net/npm/openlayers@4.6.5/dist/ol.min.js",
    "https://static.imjoy.io/spectre.css/spectre.min.css",
    "https://static.imjoy.io/spectre.css/spectre-exp.min.css",
    "https://static.imjoy.io/spectre.css/spectre-icons.min.css",
    "https://cdnjs.cloudflare.com/ajax/libs/noUiSlider/13.1.5/nouislider.min.css",
    "https://cdnjs.cloudflare.com/ajax/libs/noUiSlider/13.1.5/nouislider.min.js",
    "https://cdnjs.cloudflare.com/ajax/libs/pako/1.0.10/pako.min.js",
    "https://cdnjs.cloudflare.com/ajax/libs/upng-js/2.1.0/UPNG.min.js",
    "https://cdnjs.cloudflare.com/ajax/libs/jszip/3.2.0/jszip.min.js",
    "https://use.fontawesome.com/releases/v5.8.2/css/all.css",
    "cache:https://use.fontawesome.com/releases/v5.8.2/webfonts/fa-solid-900.woff2",
    "cache:https://images.proteinatlas.org/19661/221_G2_1_blue_red_green.jpg",
    "cache:https://images.proteinatlas.org/19663/395_C4_2_blue_red_green.jpg"
   ],
   "dependencies": [
    "oeway/ImJoy-Plugins:ImageSelection",
    "oeway/ImJoy-Plugins:Tif File Importer"
   ],
   "defaults": {
    "w": 35,
    "h": 25,
    "fullscreen": true
   },
   "cover": "https://oeway.github.io/ImJoy-Plugins/image-annotator/annotator-cover.gif",
   "uri": "imjoy-plugins/ImageAnnotator.imjoy.html"
  },
  {
   "name": "Noise2Self",
   "type": "native-python",
   "version": "0.1.9",
   "tags": [
    "CPU",
    "GPU"
   ],
   "api_version": "0.1.2",
   "description": "A demo plugin for Noise2Self (Blind Denoising by Self-Supervision)",
   "ui": "training steps:{id:'steps', type:'number', min:1, placeholder:1000}",
   "inputs": null,
   "outputs": null,
   "flags": [],
   "icon": "extension",
   "env": {
    "CPU": "conda create -n noise2self-cpu python=3.6.2",
    "GPU": "conda create -n noise2self-gpu python=3.6.2"
   },
   "requirements": {
    "CPU": [
     "repo:https://github.com/czbiohub/noise2self.git",
     "conda: -c pytorch six pillow numpy scipy pytorch=1.0 torchvision"
    ],
    "GPU": [
     "repo:https://github.com/czbiohub/noise2self.git",
     "conda: -c pytorch six pillow numpy scipy cudatoolkit=9.0 pytorch=1.0 torchvision"
    ]
   },
   "dependencies": [
    "oeway/ImJoy-Plugins:Im2Im-Dashboard"
   ],
   "uri": "imjoy-plugins/Noise2Self.imjoy.html"
  },
  {
   "name": "PyImageJ-Demo",
   "type": "native-python",
   "version": "0.1.0",
   "api_version": "0.1.2",
   "description": "This plugin process image with frangiVesselness function in ImageJ",
   "tags": [],
   "ui": "",
   "inputs": null,
   "outputs": null,
   "flags": [],
   "icon": "extension",
   "env": "conda create -n imagej2 openjdk=8",
   "requirements": [
    "conda: -c conda-forge pyimagej",
    "pip: scikit-image pillow"
   ],
   "dependencies": [],
   "uri": "imjoy-plugins/PyImageJ-Demo.imjoy.html"
  },
  {
   "name": "SchemaIO",
   "type": "window",
   "tags": [],
   "ui": "",
   "version": "0.2.6",
   "api_version": "0.1.3",
   "description": "[TODO: describe this plugin with one sentence.]",
   "icon": "extension",
   "inputs": null,
   "outputs": null,
   "env": "",
   "requirements": [
    "https://cdnjs.cloudflare.com/ajax/libs/vue/2.5.22/vue.min.js",
    "https://unpkg.com/vue-form-generator@2.3.4/dist/vfg.js",
    "https://unpkg.com/vue-form-generator@2.3.4/dist/vfg.css",
    "https://cdn.jsdelivr.net/npm/vega@5.3.4/build/vega.js",
    "https://cdn.jsdelivr.net/npm/vega-lite@3.1.0",
    "https://cdn.jsdelivr.net/npm/vega-embed@4.0.0"
   ],
   "dependencies": [],
   "defaults": {
    "w": 20,
    "h": 10
   },
   "runnable": false,
   "uri": "imjoy-plugins/SchemaIO.imjoy.html"
  },
  {
   "name": "Skin-Lesion-Analyzer",
   "type": "window",
   "tags": [],
   "ui": "A pretrained MobileNet image classifier for images of skin lesion built with Tensorflow.js",
   "version": "0.1.1",
   "api_version": "0.1.2",
   "description": "A pretrained MobileNet image classifier built with Tensorflow.js",
   "icon": "extension",
   "inputs": null,
   "outputs": null,
   "env": "",
   "requirements": [
    "https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.14.1",
    "https://unpkg.com/spectre.css/dist/spectre.min.css",
    "https://unpkg.com/spectre.css/dist/spectre-exp.min.css",
    "https://unpkg.com/spectre.css/dist/spectre-icons.min.css"
   ],
   "dependencies": [],
   "defaults": {
    "w": 15,
    "h": 20
   },
   "uri": "imjoy-plugins/Skin-Lesion-Analyzer.imjoy.html"
  },
  {
   "name": "ANNA-PALM",
   "type": "native-python",
   "version": "0.1.18",
   "api_version": "0.1.5",
   "description": "A plugin for training models with ANNA-PALM.",
   "tags": [
    "CPU",
    "GPU"
   ],
   "ui": null,
   "inputs": null,
   "outputs": null,
   "icon": null,
   "env": {
    "CPU": [
     "conda create -n annapalm-cpu python=3.6"
    ],
    "GPU": [
     "conda create -n annapalm-gpu python=3.6"
    ]
   },
   "requirements": {
    "CPU": [
     "repo:https://github.com/imodpasteur/ANNA-PALM",
     "cmd:pip install -r ANNA-PALM/requirements.txt"
    ],
    "GPU": [
     "repo:https://github.com/imodpasteur/ANNA-PALM",
     "pip: Pillow numpy==1.15.0 scipy matplotlib scikit-image tensorflow-gpu==1.8.0 gputil==1.4.0"
    ]
   },
   "dependencies": [
    "oeway/ImJoy-Plugins:Im2Im-Dashboard",
    "oeway/ImJoy-Plugins:launchpad",
    "oeway/ImJoy-Plugins:Tabbed-Docs"
   ],
   "cover": "https://imjoy-team.github.io/example-plugins/annapalm/annapalm-cover.gif",
   "uri": "imjoy-plugins/annaPalm.imjoy.html"
  },
  {
   "name": "maui-demo",
   "type": "native-python",
   "version": "0.1.0",
   "description": "A demo plugin for Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit",
   "tags": [],
   "ui": "",
   "cover": "https://imjoy-team.github.io/example-plugins/maui/maui-training.png",
   "inputs": null,
   "outputs": null,
   "flags": [],
   "icon": "extension",
   "api_version": "0.1.7",
   "env": "conda create -n maui python=3.6",
   "permissions": [],
   "requirements": [
    "maui-tools",
    "scikit-learn",
    "pandas",
    "matplotlib",
    "seaborn==0.9.0",
    "lifelines==0.14.6"
   ],
   "dependencies": [
    "oeway/ImJoy-Plugins:Im2Im-Dashboard"
   ],
   "uri": "imjoy-plugins/maui-demo.imjoy.html"
  }
 ],
 "collections": []
}