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Ben-Salmon committed Aug 23, 2024
1 parent a771440 commit 2738b3f
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12 changes: 1 addition & 11 deletions 02_Noise2Void/exercise.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"<div class=\"alert alert-block alert-success\"><h1><b>Checkpoint 1: What is N2V really doing?</b></h1>\n",
"<div class=\"alert alert-block alert-success\"><h1><b>Checkpoint 1: N2V masking</b></h1>\n",
"</div>"
]
},
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"careamist = CAREamist(source=training_config)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%load_ext tensorboard\n",
"%tensorboard --logdir logs/lightning_logs"
]
},
{
"attachments": {},
"cell_type": "markdown",
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4 changes: 2 additions & 2 deletions 03_COSDD/exercise.ipynb
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"source": [
"<img src=\"resources/explainer.png\"/>\n",
"\n",
"COSDD is a Variational Autoencoder~\\cite{chenvariational} (solid arrows) trained to model the distribution of noisy images $\\mathbf{x}$. \n",
"COSDD is a Variational Autoencoder (solid arrows) trained to model the distribution of noisy images $\\mathbf{x}$. \n",
"The autoregressive (AR) decoder models the noise component of the images, while the latent variable models only the clean signal component $\\mathbf{s}$.\n",
"In a second step (dashed arrows), the \\emph{signal decoder} is trained to map latent variables into image space, producing an estimate of the signal underlying $\\mathbf{x}$.\n",
"{\\bf b):}\n",
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"outputs": [],
"source": [
"lowsnr_path = \"./../data/mito-confocal-lowsnr.tif\"\n",
"n_test_images = 10\n",
"n_test_images = 5\n",
"# load the data\n",
"test_set = tifffile.imread(lowsnr_path)\n",
"test_set = test_set[:n_test_images, np.newaxis]\n",
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2 changes: 1 addition & 1 deletion 04_DenoiSplit/exercise.ipynb
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},
{
"cell_type": "markdown",
"id": "4d103864",
"id": "fc2ed8e0",
"metadata": {},
"source": [
"<hr style=\"height:2px;\"><div class=\"alert alert-block alert-success\"><h1>End of the exercise</h1>\n",
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