test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from PIL import Image\n",
    "import matplotlib.pyplot as plt \n",
    "import numpy as np \n",
    "img=Image.open(\"/opt/data/private/BairdWorkspace/SegResearchToolkit/data/optic_disc_seg/Annotations/H0002.png\")\n",
    "plt.imshow(img)\n",
    "print(np.unique(img))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "import os \n",
    "images_list=os.listdir(\"/opt/data/private/BairdWorkspace/Seg/SegResearchToolkit/output/result/added_prediction\")\n",
    "images=[Image.open(\"/opt/data/private/BairdWorkspace/Seg/SegResearchToolkit/output/result/added_prediction/\"+x) for x in images_list]\n",
    "gif=images[0]\n",
    "gif.save(\"/opt/data/private/BairdWorkspace/Seg/SegResearchToolkit/predict.gif\",format=\"gif\",save_all=True,append_images=images[1:])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "segall",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}