{ "cells": [ { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [], "source": [ "import PIL\n", "from PIL import Image, ImageEnhance, ImageDraw, ImageFont\n", "from IPython.display import display\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": [ "img = Image.open('download.png')" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(img)" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(659, 821)" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img.size" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "re_img = img.resize((300,300))\n", "re_img.save('mo_img.png')\n", "mo_img = Image.open('mo_img.png')\n", "display(mo_img)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": [ "from numpy import asarray" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": [ "data = asarray(mo_img)" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "numpy.ndarray" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(data)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(300, 300, 4)" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.shape" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[[0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " ...,\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0]],\n", "\n", " [[0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " ...,\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0]],\n", "\n", " [[0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " ...,\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0]],\n", "\n", " ...,\n", "\n", " [[0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " ...,\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0]],\n", "\n", " [[0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " ...,\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0]],\n", "\n", " [[0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " ...,\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0],\n", " [0, 0, 0, 0]]], dtype=uint8)" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "data_1 = data" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "from numpy import sum" ] }, { "cell_type": "code", "execution_count": 221, "metadata": {}, "outputs": [ { "ename": "IndexError", "evalue": "index 74 is out of bounds for axis 0 with size 74", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mmy_list\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmy_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mIndexError\u001b[0m: index 74 is out of bounds for axis 0 with size 74" ] } ], "source": [ "my_list =[]\n", "for i in range(300): \n", " my_list.append((sum(data_1[i])))" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 0.0,\n", " 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281,\n", " 282,\n", " 283,\n", " 284,\n", " 285,\n", " 286,\n", " 287,\n", " 288,\n", " 289,\n", " 290,\n", " 291,\n", " 292,\n", " 293,\n", " 294,\n", " 295,\n", " 296,\n", " 297,\n", " 298,\n", " 299]" ] }, "execution_count": 72, "metadata": {}, "output_type": "execute_result" } ], "source": [ "my_rows" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(my_rows,my_list)" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(mo_img.crop((0,39,300,76)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [], "source": [ "def getRow(mylist):\n", " i=0\n", " while(mylist[i]==0.0):\n", " i=i+1\n", " print(i)\n", " j=i\n", " while(mylist[j]!=0.0):\n", " j=j+1\n", " print(j)" ] }, { "cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "39\n", "76\n" ] } ], "source": [ "getRow(my_list)" ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [], "source": [ "line_img = mo_img.crop((0,39,300,76))" ] }, { "cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(300, 37)" ] }, "execution_count": 107, "metadata": {}, "output_type": "execute_result" } ], "source": [ "line_img.size" ] }, { "cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "line_img" ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [], "source": [ "line_img.save('line_img.png')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# word segmentation starts" ] }, { "cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "execution_count": 143, "metadata": {}, "output_type": "execute_result" } ], "source": [ "line_img" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [], "source": [ "from numpy import asarray" ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [], "source": [ "data = asarray(line_img)" ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(37, 300, 4)" ] }, "execution_count": 146, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.shape" ] }, { "cell_type": "code", "execution_count": 166, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0,\n", " 1,\n", " 2,\n", " 3,\n", " 4,\n", " 5,\n", " 6,\n", " 7,\n", " 8,\n", " 9,\n", " 10,\n", " 11,\n", " 12,\n", " 13,\n", " 14,\n", " 15,\n", " 16,\n", " 17,\n", " 18,\n", " 19,\n", " 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"execution_count": 166, "metadata": {}, "output_type": "execute_result" } ], "source": [ "my_cols = []\n", "for i in range(300):\n", " my_cols.append(i)\n", "my_cols\n" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(37, 300, 4)" ] }, "execution_count": 148, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.shape" ] }, { "cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [], "source": [ "data_1=data.reshape(74,600)" ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[0, 0, 0, ..., 0, 0, 0],\n", " [0, 0, 0, ..., 0, 0, 0],\n", " [0, 0, 0, ..., 0, 0, 0],\n", " ...,\n", " [0, 0, 0, ..., 0, 0, 0],\n", " [0, 0, 0, ..., 0, 0, 0],\n", " [0, 0, 0, ..., 0, 0, 0]], dtype=uint8)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(data_1)" ] }, { "cell_type": "code", "execution_count": 196, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 0, 0, 0, 34], dtype=uint8)" ] }, "execution_count": 196, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[10][98]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 219, "metadata": {}, "outputs": [], "source": [ "my_col_list =[]\n", "for j in range(300):\n", " for i in range(37):\n", " col_list_1=[]\n", " col_list_1.append(data[i][j][3])\n", " my_col_list.append((sum(col_list_1)))\n", " " ] }, { "cell_type": "code", "execution_count": 220, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 0,\n", " 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(my_cols,my_col_list)" ] }, { "cell_type": "code", "execution_count": 203, "metadata": {}, "outputs": [], "source": [ "def getCol(mylist):\n", " i=0\n", " while(mylist[i]==0.0):\n", " i=i+1\n", " print(i)\n", " j=i\n", " while(mylist[j]!=0.0):\n", " j=j+1\n", " print(j)" ] }, { "cell_type": "code", "execution_count": 206, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "97\n", "110\n" ] } ], "source": [ "getCol(my_col_list)" ] }, { "cell_type": "code", "execution_count": 208, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(300, 37)" ] }, "execution_count": 208, "metadata": {}, "output_type": "execute_result" } ], "source": [ "line_img.size" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "display(line_img.crop())" ] }, { "cell_type": "code", "execution_count": 222, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(mo_img.crop((97,39,110,76)))" ] }, { "cell_type": "code", "execution_count": 235, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(mo_img.crop((97,39,123,76)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 236, "metadata": {}, "outputs": [], "source": [ "final_img = mo_img.crop((97,39,123,76))" ] }, { "cell_type": "code", "execution_count": 237, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "execution_count": 237, "metadata": {}, "output_type": "execute_result" } ], "source": [ "final_img" ] }, { "cell_type": "code", "execution_count": 238, "metadata": {}, "outputs": [], "source": [ "final_img.save('final_img.png')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }