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image-compression
Commit a9bf04b8 authored by Bryce Hepner's avatar Bryce Hepner
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Modified in running, tests successful

parent 9c9419fe
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Showing with 293 additions and 81 deletions
Encoding_decoding.ipynb
View file @ a9bf04b8
...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 2,
"id": "14f74f21", "id": "14f74f21",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -24,7 +24,7 @@ ...@@ -24,7 +24,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 3,
"id": "c16af61f", "id": "c16af61f",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -77,7 +77,7 @@ ...@@ -77,7 +77,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 4,
"id": "53786325", "id": "53786325",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -153,7 +153,7 @@ ...@@ -153,7 +153,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 5,
"id": "6b965751", "id": "6b965751",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -209,7 +209,7 @@ ...@@ -209,7 +209,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 6,
"id": "b7561883", "id": "b7561883",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -318,7 +318,7 @@ ...@@ -318,7 +318,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 7,
"id": "2eb774d2", "id": "2eb774d2",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -358,7 +358,7 @@ ...@@ -358,7 +358,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 8,
"id": "8eeb40d0", "id": "8eeb40d0",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -402,6 +402,9 @@ ...@@ -402,6 +402,9 @@
" # if it's the very first pixel on the image\n", " # if it's the very first pixel on the image\n",
" if i == 0 and j == 0:\n", " if i == 0 and j == 0:\n",
" decode_matrix[i][j] = int(the_keys0[the_values0.index(encoded_matrix[i,j])])\n", " decode_matrix[i][j] = int(the_keys0[the_values0.index(encoded_matrix[i,j])])\n",
" print(encoded_matrix[i][j])\n",
" print(the_values0.index(encoded_matrix[i,j]))\n",
" print(int(the_keys0[the_values0.index(encoded_matrix[i,j])]))\n",
" # if it's on the boundary (any of the 4 edges)\n", " # if it's on the boundary (any of the 4 edges)\n",
" elif i == 0 or i == decode_matrix.shape[0]-1 or j == 0 or j == decode_matrix.shape[1]-1:\n", " elif i == 0 or i == decode_matrix.shape[0]-1 or j == 0 or j == decode_matrix.shape[1]-1:\n",
" decode_matrix[i][j] = int(the_keys0[the_values0.index(encoded_matrix[i,j])]) + decode_matrix[0][0]\n", " decode_matrix[i][j] = int(the_keys0[the_values0.index(encoded_matrix[i,j])]) + decode_matrix[0][0]\n",
...@@ -442,7 +445,7 @@ ...@@ -442,7 +445,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 15, "execution_count": 9,
"id": "f959fe93", "id": "f959fe93",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
...@@ -506,7 +509,7 @@ ...@@ -506,7 +509,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 12, "execution_count": 10,
"id": "3e0e9742", "id": "3e0e9742",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
...@@ -514,6 +517,9 @@ ...@@ -514,6 +517,9 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"11100100000\n",
"499\n",
"22275\n",
"True\n", "True\n",
"5\n" "5\n"
] ]
......
SaveableEncoderDecoder.ipynb
View file @ a9bf04b8
...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -20,7 +20,7 @@ ...@@ -20,7 +20,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -72,7 +72,7 @@ ...@@ -72,7 +72,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -147,7 +147,7 @@ ...@@ -147,7 +147,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 119,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -197,12 +197,19 @@ ...@@ -197,12 +197,19 @@
"\n", "\n",
" #There is a huge memory leak here, no idea how or why\n", " #There is a huge memory leak here, no idea how or why\n",
" nodes = sorted(nodes, key=lambda x: x[1], reverse=True)\n", " nodes = sorted(nodes, key=lambda x: x[1], reverse=True)\n",
" return nodes[0][0]" " return nodes[0][0]\n",
"def decode_string(huffman_string, the_values, the_keys):\n",
" for i in range(len(huffman_string)):\n",
" try:\n",
" return (int(the_keys[the_values.index(huffman_string[:i+1])]),huffman_string[i+1:])\n",
" except:\n",
" pass\n",
" "
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 120,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -310,7 +317,7 @@ ...@@ -310,7 +317,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 121,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -350,11 +357,11 @@ ...@@ -350,11 +357,11 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 133,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"def decoder(A, encoded_matrix, list_dic, bins, use_diff):\n", "def decoder(A, encoded_string, list_dic, bins, use_diff):\n",
" \"\"\"\n", " \"\"\"\n",
" This function decodes the encoded_matrix.\n", " This function decodes the encoded_matrix.\n",
" Input:\n", " Input:\n",
...@@ -392,10 +399,13 @@ ...@@ -392,10 +399,13 @@
" for j in range(decode_matrix.shape[1]):\n", " for j in range(decode_matrix.shape[1]):\n",
" # if it's the very first pixel on the image\n", " # if it's the very first pixel on the image\n",
" if i == 0 and j == 0:\n", " if i == 0 and j == 0:\n",
" decode_matrix[i][j] = int(the_keys0[the_values0.index(encoded_matrix[i,j])])\n", " colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys0, the_values=the_values0)\n",
" decode_matrix[i][j] = colorvalue\n",
" \n",
" # if it's on the boundary (any of the 4 edges)\n", " # if it's on the boundary (any of the 4 edges)\n",
" elif i == 0 or i == decode_matrix.shape[0]-1 or j == 0 or j == decode_matrix.shape[1]-1:\n", " elif i == 0 or i == decode_matrix.shape[0]-1 or j == 0 or j == decode_matrix.shape[1]-1:\n",
" decode_matrix[i][j] = int(the_keys0[the_values0.index(encoded_matrix[i,j])]) + decode_matrix[0][0]\n", " colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys0, the_values=the_values0)\n",
" decode_matrix[i][j] = colorvalue + decode_matrix[0][0]\n",
" # if not the boundary\n", " # if not the boundary\n",
" else:\n", " else:\n",
" # predict the image with the known pixel value\n", " # predict the image with the known pixel value\n",
...@@ -419,13 +429,17 @@ ...@@ -419,13 +429,17 @@
" # add on the difference by searching the dictionary\n", " # add on the difference by searching the dictionary\n",
" # !!!!!WARNING!!!! has to change this part, eveytime you change the number of bins\n", " # !!!!!WARNING!!!! has to change this part, eveytime you change the number of bins\n",
" if difference <= bins[0]:\n", " if difference <= bins[0]:\n",
" decode_matrix[i][j] = int(the_keys1[the_values1.index(encoded_matrix[i,j])]) + int(predict)\n", " colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys1, the_values=the_values1)\n",
" decode_matrix[i][j] = colorvalue + int(predict)\n",
" elif difference <= bins[1] and difference > bins[0]:\n", " elif difference <= bins[1] and difference > bins[0]:\n",
" decode_matrix[i][j] = int(the_keys2[the_values2.index(encoded_matrix[i,j])]) + int(predict)\n", " colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys2, the_values=the_values2)\n",
" decode_matrix[i][j] = colorvalue + int(predict)\n",
" elif difference <= bins[2] and difference > bins[1]:\n", " elif difference <= bins[2] and difference > bins[1]:\n",
" decode_matrix[i][j] = int(the_keys3[the_values3.index(encoded_matrix[i,j])]) + int(predict)\n", " colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys3, the_values=the_values3)\n",
" decode_matrix[i][j] = colorvalue + int(predict)\n",
" else:\n", " else:\n",
" decode_matrix[i][j] = int(the_keys4[the_values4.index(encoded_matrix[i,j])]) + int(predict)\n", " colorvalue, encoded_string = decode_string(encoded_string,the_keys=the_keys4, the_values=the_values4)\n",
" decode_matrix[i][j] = colorvalue + int(predict)\n",
" \n", " \n",
" \n", " \n",
" return decode_matrix.astype(int)" " return decode_matrix.astype(int)"
...@@ -433,35 +447,227 @@ ...@@ -433,35 +447,227 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": 134,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [
"def compress_rate(image_array, new_error, diff, bound, huffman_encoding_list, bins):\n",
" '''\n",
" This function is used to calculate the compression rate.\n",
" Input:\n",
" image_array (512, 640): original_core image\n",
" new_error (512, 640): error that includes the boundary\n",
" diff (510, 638): difference of min and max of the 4 neighbors\n",
" bound (2300,): the boundary values after subtracting the very first pixel value\n",
" huffman_encoding_list (num_dic + 1,): a list of huffman coding table \n",
" bins (num_bins - 1,): a list of threshold to cut the bins\n",
" \n",
" Return:\n",
" compression rate\n",
" '''\n",
" # the bits for the original image\n",
" o_len = 0\n",
" # the bits for the compressed image\n",
" c_len = 0\n",
" # initializing the varible \n",
" \n",
" #this was unused\n",
" # im = np.reshape(image,(512, 640))\n",
" \n",
" real_boundary = np.hstack((image_array[0,:],image_array[-1,:],image_array[1:-1,0],image_array[1:-1,-1]))\n",
" #Bryce's notes: Why are they all reshaped?\n",
" original_core = image_array[1:-1,1:-1].reshape(-1)\n",
" diff = diff.reshape(-1)\n",
" error = new_error[1:-1,1:-1].reshape(-1)\n",
" \n",
" # calculate the bit for boundary\n",
" for i in range(0,len(bound)):\n",
" o_len += len(bin(real_boundary[i])[2:])\n",
" c_len += len(huffman_encoding_list[0][str(bound[i])])\n",
" \n",
" # calculate the bit for the pixels inside the boundary\n",
" for i in range(0,len(original_core)):\n",
"\n",
" # for the original image\n",
" o_len += len(bin(original_core[i])[2:])\n",
" \n",
" # check the difference and find the coresponding huffman table\n",
" # !!!!!WARNING!!!! has to change this part, eveytime you change the number of bins\n",
" if diff[i] <= bins[0]:\n",
" c_len += len(huffman_encoding_list[1][str(int(error[i]))])\n",
" \n",
" elif diff[i] <= bins[1] and diff[i] > bins[0]:\n",
" c_len += len(huffman_encoding_list[2][str(int(error[i]))])\n",
" \n",
" elif diff[i] <= bins[2] and diff[i] > bins[1]:\n",
" c_len += len(huffman_encoding_list[3][str(int(error[i]))])\n",
"\n",
" else: \n",
" c_len += len(huffman_encoding_list[4][str(int(error[i]))])\n",
" \n",
" return c_len/o_len"
]
},
{
"cell_type": "code",
"execution_count": 136,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n",
"5\n"
]
}
],
"source": [ "source": [
"scenes = file_extractor()\n", "scenes = file_extractor()\n",
"images = image_extractor(scenes)\n", "images = image_extractor(scenes)\n",
"list_dic, image, new_error, diff, bound, predict, bins, A = huffman(images[0], 4, False)\n", "list_dic, image, new_error, diff, bound, predict, bins, A = huffman(images[0], 4, False)\n",
"encoded_string = encoder(new_error, list_dic, diff, bound, bins)" "encoded_string = encoder(new_error, list_dic, diff, bound, bins)\n",
"reconstruct_image = decoder(A, encoded_string, list_dic, bins, False)\n",
"print(np.allclose(image, reconstruct_image))\n",
"print(len(list_dic))\n"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10, "execution_count": 131,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"ename": "NameError", "data": {
"evalue": "name 'encoded_string' is not defined", "text/plain": [
"output_type": "error", "0.4232928466796875"
"traceback": [ ]
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", },
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "execution_count": 131,
"\u001b[1;32m/home/bryce/git/master/SaveableEncoderDecoder.ipynb Cell 8'\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> <a href='vscode-notebook-cell:/home/bryce/git/master/SaveableEncoderDecoder.ipynb#ch0000007?line=0'>1</a>\u001b[0m \u001b[39mprint\u001b[39m(encoded_string)\n", "metadata": {},
"\u001b[0;31mNameError\u001b[0m: name 'encoded_string' is not defined" "output_type": "execute_result"
}
],
"source": [
"compress_rate(image, new_error, diff, bound, list_dic, bins)"
]
},
{
"cell_type": "code",
"execution_count": 149,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2080618\n"
] ]
} }
], ],
"source": [ "source": [
"print(encoded_string)" "print(sys.getsizeof(encoded_string))\n",
"with open(\"MatrixNowString.txt\", 'wb') as f:\n",
" f.write(bytearray(encoded_string, encoding = 'utf8'))"
]
},
{
"cell_type": "code",
"execution_count": 140,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"657197\n"
]
}
],
"source": [
"print(os.path.getsize('images/1626032610_393963/1626032610_393963_0.tiff'))"
]
},
{
"cell_type": "code",
"execution_count": 169,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"398145\n"
]
}
],
"source": [
"print(os.path.getsize('MatrixNowString.txt'))"
]
},
{
"cell_type": "code",
"execution_count": 167,
"metadata": {},
"outputs": [],
"source": [
"def bitstring_to_bytes(s):\n",
" v = int(s, 2)\n",
" b = bytearray()\n",
" while v:\n",
" b.append(v & 0xff)\n",
" v >>= 8\n",
" return bytes(b[::-1])\n",
"\n",
"s = \"0110100001101001\"\n",
"inletters = bitstring_to_bytes(encoded_string)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 168,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2080618\n"
]
}
],
"source": [
"print(sys.getsizeof(encoded_string))\n",
"with open(\"MatrixNowString.txt\", 'w') as f:\n",
" f.write(inletters.decode(\"ISO-8859-1\"))"
]
},
{
"cell_type": "code",
"execution_count": 172,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.6058229115470704"
]
},
"execution_count": 172,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(os.path.getsize('MatrixNowString.txt'))/os.path.getsize('images/1626032610_393963/1626032610_393963_0.tiff')"
] ]
}, },
{ {
......
compression_benchmark.ipynb
View file @ a9bf04b8
...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 46, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -33,7 +33,7 @@ ...@@ -33,7 +33,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 47, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -61,7 +61,7 @@ ...@@ -61,7 +61,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 48, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -71,7 +71,7 @@ ...@@ -71,7 +71,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 49, "execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -90,7 +90,7 @@ ...@@ -90,7 +90,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 50, "execution_count": 6,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -99,7 +99,7 @@ ...@@ -99,7 +99,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 51, "execution_count": 7,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -108,7 +108,7 @@ ...@@ -108,7 +108,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 52, "execution_count": 8,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -117,7 +117,7 @@ ...@@ -117,7 +117,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 53, "execution_count": 9,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -134,7 +134,7 @@ ...@@ -134,7 +134,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 54, "execution_count": 10,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -152,7 +152,7 @@ ...@@ -152,7 +152,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 55, "execution_count": 11,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -161,7 +161,7 @@ ...@@ -161,7 +161,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 56, "execution_count": 12,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -178,7 +178,7 @@ ...@@ -178,7 +178,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 57, "execution_count": 13,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -196,7 +196,7 @@ ...@@ -196,7 +196,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 58, "execution_count": 14,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -213,35 +213,46 @@ ...@@ -213,35 +213,46 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 64, "execution_count": 15,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"from PIL import TiffTags\n", "from PIL import TiffTags\n",
"TiffTags.LIBTIFF_CORE.add(317)\n", "TiffTags.LIBTIFF_CORE.add(318)\n",
"picture.save('Compressed_Round_2.tiff', compression='tiff_lzw', tiffinfo={317: 2})" "picture.save('Compressed_Round_2.tiff', compression='tiff_lzw', tiffinfo={317: 2})"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 65, "execution_count": 16,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"404176\n" "404176\n",
"True\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/bryce/.local/lib/python3.8/site-packages/PIL/TiffImagePlugin.py:845: UserWarning: Truncated File Read\n",
" warnings.warn(str(msg))\n"
] ]
} }
], ],
"source": [ "source": [
"print(os.path.getsize('Compressed_Round_2.tiff'))" "print(os.path.getsize('Compressed_Round_2.tiff'))\n",
"potentially_compressed = Image.open('Compressed_Round_2.tiff')\n",
"print(np.allclose(picture,potentially_compressed))"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 66, "execution_count": 16,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -274,14 +285,14 @@ ...@@ -274,14 +285,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 71, "execution_count": 17,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"<PIL.TiffImagePlugin.TiffImageFile image mode=I;16B size=640x513 at 0x7F3520192160>\n" "(640, 513)\n"
] ]
} }
], ],
...@@ -295,7 +306,7 @@ ...@@ -295,7 +306,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 68, "execution_count": 18,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -304,7 +315,7 @@ ...@@ -304,7 +315,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 72, "execution_count": 19,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -337,7 +348,7 @@ ...@@ -337,7 +348,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 98, "execution_count": 20,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -346,7 +357,7 @@ ...@@ -346,7 +357,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 113, "execution_count": 21,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -373,7 +384,7 @@ ...@@ -373,7 +384,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 109, "execution_count": 22,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -383,7 +394,7 @@ ...@@ -383,7 +394,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 111, "execution_count": 23,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -392,24 +403,24 @@ ...@@ -392,24 +403,24 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 114, "execution_count": 24,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"0.31142564558267916\n" "0.6885743544173208\n"
] ]
} }
], ],
"source": [ "source": [
"print((oldsize-thirdsize)/oldsize)" "print((thirdsize)/oldsize)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 115, "execution_count": 25,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -418,7 +429,7 @@ ...@@ -418,7 +429,7 @@
"452578" "452578"
] ]
}, },
"execution_count": 115, "execution_count": 25,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -429,20 +440,9 @@ ...@@ -429,20 +440,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 116, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"data": {
"text/plain": [
"112"
]
},
"execution_count": 116,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [] "source": []
}, },
{ {
......
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