Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-label-image-classification
Languages:
English
Size:
1K<n<10K
License:
File size: 847 Bytes
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Split data into normal and abnormal fundus photo\n",
"import pandas as pd\n",
"\n",
"label_df = pd.read_csv(\"RFMiD_Training_Labels.csv\")\n",
"label_df.head()\n",
"\n",
"import shutil\n",
"\n",
"for index,row in label_df.iterrows():\n",
" at_risk = row['Disease_Risk']\n",
" file = str(row[\"ID\"])+\".png\"\n",
" path = \"Training\"\n",
" file_path = path+\"/\"+file\n",
"\n",
" if not at_risk:\n",
" shutil.copy(file_path, \"../normal/\")\n",
" else:\n",
" shutil.copy(file_path, \"../abnormal/\")"
]
}
],
"metadata": {
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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