{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "9fe071ae-a71d-4464-aeb3-11317319ddda",
"metadata": {},
"outputs": [],
"source": [
"import pyclesperanto_prototype as cle\n",
"from napari_segment_blobs_and_things_with_membranes import local_minima_seeded_watershed\n",
"from skimage.data import cells3d\n",
"import stackview\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "16f1e666-5a67-4194-85c3-e880aa7f6d9e",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"\n",
" \n",
" | \n",
"\n",
"cle._ image \n",
"\n",
"shape | (256, 256) | \n",
"dtype | uint16 | \n",
"size | 128.0 kB | \n",
"min | 277.0 | max | 44092.0 | \n",
" \n",
" \n",
" | \n",
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\n",
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],
"text/plain": [
"cl.OCLArray([[4496, 5212, 6863, ..., 2917, 2680, 2642],\n",
" [4533, 5146, 7555, ..., 2843, 2857, 2748],\n",
" [4640, 6082, 8452, ..., 3372, 3039, 3128],\n",
" ...,\n",
" [1339, 1403, 1359, ..., 4458, 4314, 4795],\n",
" [1473, 1560, 1622, ..., 3967, 4531, 4204],\n",
" [1380, 1368, 1649, ..., 3091, 3558, 3682]], dtype=uint16)"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"image = cle.asarray(cells3d()[30, 0]).astype(np.uint16) \n",
"\n",
"image"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "ad1af5ee-8d49-407e-a804-62238fb90e75",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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"nsbatwm made image \n",
"\n",
"shape | (256, 256) | \n",
"dtype | int32 | \n",
"size | 256.0 kB | \n",
"min | 1 | max | 35 | \n",
" \n",
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"text/plain": [
"StackViewNDArray([[ 5, 5, 5, ..., 3, 3, 3],\n",
" [ 5, 5, 5, ..., 3, 3, 3],\n",
" [ 5, 5, 5, ..., 3, 3, 3],\n",
" ...,\n",
" [32, 32, 32, ..., 35, 35, 35],\n",
" [32, 32, 32, ..., 35, 35, 35],\n",
" [32, 32, 32, ..., 35, 35, 35]])"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"labels = local_minima_seeded_watershed(image, spot_sigma=5)\n",
"labels"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "76e70e62-8bf2-48f4-ab3f-19c2e9207a57",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "1f4ec0560da1412a85a5ec8b344c282f",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=256, width=256),)),)), Label(value='[]:')))"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"stackview.picker(labels)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "70769d97-628c-4aa0-b766-91346ad67677",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3171.804\n"
]
}
],
"source": [
"tmi = cle.generate_touch_mean_intensity_matrix(image, labels)\n",
"print(tmi[13,15])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a7b51db9-2b0e-482c-911e-c10735030bc4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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" \n",
" | \n",
"\n",
"cle._ image \n",
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"shape | (256, 256) | \n",
"dtype | uint32 | \n",
"size | 256.0 kB | \n",
"min | 1.0 | max | 33.0 | \n",
" \n",
"\n",
" | \n",
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"
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],
"text/plain": [
"cl.OCLArray([[ 5, 5, 5, ..., 3, 3, 3],\n",
" [ 5, 5, 5, ..., 3, 3, 3],\n",
" [ 5, 5, 5, ..., 3, 3, 3],\n",
" ...,\n",
" [31, 31, 31, ..., 33, 33, 33],\n",
" [31, 31, 31, ..., 33, 33, 33],\n",
" [31, 31, 31, ..., 33, 33, 33]], dtype=uint32)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cle.merge_labels_with_border_intensity_within_range(image, labels, maximum_intensity=2000)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "6f49b9c8-c577-422e-a693-7c715055760d",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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"dtype | uint32 | \n",
"size | 256.0 kB | \n",
"min | 1.0 | max | 32.0 | \n",
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"text/plain": [
"cl.OCLArray([[ 5, 5, 5, ..., 3, 3, 3],\n",
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" [ 5, 5, 5, ..., 3, 3, 3],\n",
" ...,\n",
" [30, 30, 30, ..., 32, 32, 32],\n",
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" [30, 30, 30, ..., 32, 32, 32]], dtype=uint32)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cle.merge_labels_with_border_intensity_within_range(image, labels, maximum_intensity=3000)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "d1708789-72d3-40fa-a89b-1afd64f4b422",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
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"\n",
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" | \n",
"\n",
"cle._ image \n",
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"dtype | uint32 | \n",
"size | 256.0 kB | \n",
"min | 1.0 | max | 21.0 | \n",
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"text/plain": [
"cl.OCLArray([[ 5, 5, 5, ..., 3, 3, 3],\n",
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" [ 5, 5, 5, ..., 3, 3, 3],\n",
" ...,\n",
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" [20, 20, 20, ..., 21, 21, 21]], dtype=uint32)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cle.merge_labels_with_border_intensity_within_range(image, labels, maximum_intensity=5000)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f98e0001-0542-4848-973e-c3c9820d6c58",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"cl.OCLArray([[7, 7, 7, ..., 3, 3, 3],\n",
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" ...,\n",
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"execution_count": 9,
"metadata": {},
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}
],
"source": [
"cle.merge_labels_with_border_intensity_within_range(image, labels, maximum_intensity=8000)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b8b2384d-7c71-4c04-90c3-1ad108c12bec",
"metadata": {},
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}
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