{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a3907dd6",
   "metadata": {},
   "source": [
    "# Read your first image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "17dc4cd8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-01T06:45:07.567506Z",
     "iopub.status.busy": "2026-11-01T06:45:07.567352Z",
     "iopub.status.idle": "2026-11-01T06:45:08.359452Z",
     "shell.execute_reply": "2026-11-01T06:45:08.358350Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(8, 3))\n",
    "plt.imshow(plt.imread(\"sample.png\"))\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c6dd1f2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-11-01T06:45:08.360916Z",
     "iopub.status.busy": "2026-11-01T06:45:08.360720Z",
     "iopub.status.idle": "2026-11-01T06:45:30.986387Z",
     "shell.execute_reply": "2026-11-01T06:45:30.985525Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loaded DBNet detector (CPU, threads=8)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loaded SVTR recognizer (vocab=185 chars, CPU, threads=8)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[occular] LM (pure Python): compact_lm.npz (268 MB), unigrams=2010937, alpha=0.5 beta=1.0 beam=100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INVOICE147\n",
      "Paper:2packs\n",
      "Total:200.00\n"
     ]
    }
   ],
   "source": [
    "from occular import ocr\n",
    "\n",
    "text = ocr(\"sample.png\")\n",
    "print(text)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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",
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