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Auto-commit: Mon Sep 9 14:07:42 CDT 2024
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jnaiman committed Sep 9, 2024
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41 changes: 39 additions & 2 deletions _site/week03/inClass_week03.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -1401,13 +1401,50 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 87,
"id": "53987258-a45f-4a74-9550-dd7a144c1bc3",
"metadata": {},
"outputs": [],
"source": [
"n"
"#np.unique(im2_data[:,:,0]) # unique reds"
]
},
{
"cell_type": "code",
"execution_count": 89,
"id": "d3b1afad-211b-48d5-9fd5-b5ffe12aa917",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 300x300 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"imgplot = im2_data.copy() # an image we can mess with a bit\n",
"\n",
"mask = im2_data[:,:,0]<10 # low channel\n",
"imgplot[~mask] = 0 # counts on there being an alpha-channel to make things see-through\n",
"\n",
"fig, ax = plt.subplots(figsize=(3,3))\n",
"ax.set_facecolor('cyan')\n",
"ax.imshow(imgplot)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "56b1d208-e3d4-4b96-9972-0c5a19e0188c",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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