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danjacobellis
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cell-microscopy-mae

Image Feature Extraction
biology
medical
Model card Files
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Jacobellis Dan (dgj335) commited on
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  2. README.md +41 -26
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README.ipynb CHANGED
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  {
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  "cell_type": "code",
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  "id": "ec5fceef-3c7e-4f7f-8cee-802f0b08f53a",
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  "metadata": {},
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  "outputs": [
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  "text": [
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  "[NbConvertApp] Converting notebook README.ipynb to markdown\n",
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  "[NbConvertApp] Support files will be in README_files/\n",
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- "[NbConvertApp] Making directory README_files\n",
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- "[NbConvertApp] Writing 7092 bytes to README.md\n"
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  ]
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  ],
 
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  "cells": [
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+ {
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+ "cell_type": "raw",
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+ "id": "a5015ad6-39ff-4805-85b2-4a962ce0f97a",
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+ "metadata": {},
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+ "source": [
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+ "---\n",
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+ "datasets:\n",
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+ "- danjacobellis/cell_seg_labeled\n",
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+ "- danjacobellis/cell_seg\n",
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+ "pipeline_tag: image-feature-extraction\n",
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+ "tags:\n",
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+ "- biology\n",
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+ "- medical\n",
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+ "---"
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+ ]
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+ },
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  "cell_type": "code",
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  "id": "ec5fceef-3c7e-4f7f-8cee-802f0b08f53a",
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  "metadata": {},
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  "outputs": [
 
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  "text": [
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  "[NbConvertApp] Converting notebook README.ipynb to markdown\n",
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  "[NbConvertApp] Support files will be in README_files/\n",
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+ "[NbConvertApp] Writing 7517 bytes to README.md\n"
 
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README.md CHANGED
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  ```python
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  import torch
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  import numpy as np
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  ```python
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  device = "cpu"
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- checkpoint = torch.load("mae_e8000.pt",map_location="cpu")
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  args = checkpoint['args']
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  args.crops_per_sample = 1
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  ```python
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-
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  ```
 
 
 
 
 
 
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+ ---
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+ datasets:
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+ - danjacobellis/cell_seg_labeled
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+ - danjacobellis/cell_seg
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+ pipeline_tag: image-feature-extraction
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+ tags:
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+ - biology
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+ - medical
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+ ---
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+
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  ```python
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  import torch
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  import numpy as np
 
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  ```python
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  device = "cpu"
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+ checkpoint = torch.load("v0.0.1.pt",map_location="cpu")
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  args = checkpoint['args']
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  args.crops_per_sample = 1
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  ```python
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+ !jupyter nbconvert --to markdown README.ipynb
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  ```
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+
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+ [NbConvertApp] Converting notebook README.ipynb to markdown
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+ [NbConvertApp] Support files will be in README_files/
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+ [NbConvertApp] Writing 7517 bytes to README.md
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+
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