HPASingleCellTriton.imjoy.html

<docs lang="markdown">
[TODO: write documentation for this plugin.]
</docs>

<config lang="json">
{
  "name": "HPASingleCellTriton",
  "type": "web-python",
  "version": "0.1.0",
  "description": "[TODO: describe this plugin with one sentence.]",
  "tags": [],
  "ui": "",
  "cover": "",
  "inputs": null,
  "outputs": null,
  "flags": [],
  "icon": "extension",
  "api_version": "0.1.8",
  "env": "",
  "permissions": [],
  "requirements": ["imageio", "pillow", "pyotritonclient"],
  "dependencies": []
}
</config>

<script lang="python">
from imjoy import api
from js import fetch
import io
import numpy as np
import imageio
from PIL import Image
from pyotritonclient import get_config, execute_model

LABELS = {
  0: 'Nucleoplasm',
  1: 'Nuclear membrane',
  2: 'Nucleoli',
  3: 'Nucleoli fibrillar center',
  4: 'Nuclear speckles',
  5: 'Nuclear bodies',
  6: 'Endoplasmic reticulum',
  7: 'Golgi apparatus',
  8: 'Intermediate filaments',
  9: 'Actin filaments',
  10: 'Microtubules',
  11: 'Mitotic spindle',
  12: 'Centrosome',
  13: 'Plasma membrane',
  14: 'Mitochondria',
  15: 'Aggresome',
  16: 'Cytosol',
  17: 'Vesicles and punctate cytosolic patterns',
  18: 'Negative',
}

COLORS =  ["red", "green", "blue", "yellow"]
async def get_image(image_id):
    crops = []
    for color in COLORS:
        response = await fetch(f'https://images.proteinatlas.org/{image_id}_{color}.jpg')
        bytes = await response.arrayBuffer()
        bytes = bytes.to_py()
        buffer = io.BytesIO(bytes)
        buffer.name = '672_E2_1_blue_red_green.jpg'
        img = imageio.imread(buffer)
        image = Image.fromarray(img)
        image = image.resize(size=(340, 340)).convert('L')
        image = np.array(image)
        crop = image[60:188, 120:248]
        crops.append(crop)
    image = np.stack(crops, axis=0)
    assert image.shape == (4, 128, 128)
    return image

async def predict_hpa_image(image_id, threshold=0.5):
    image = await get_image('115/672_E2_1')
    config = await get_config('https://triton.imjoy.io', 'bestfitting-inceptionv3-single-cell')
    results = await execute_model([image.astype('float32')/255], config=config)
    classes = results['classes']
    pred = [(LABELS[i], prob) for i, prob in enumerate(classes.tolist()) if prob>threshold]
    return image, pred

class ImJoyPlugin():
    def setup(self):
        api.log('initialized')

    async def run(self, ctx):
        image_id = await api.prompt('Type HPA image id', '115/672_E2_1')
        image, pred = await predict_hpa_image(image_id)
        await api.alert(f'Prediction: {pred}')

api.export(ImJoyPlugin())
</script>