984 lines
1.2 MiB
Plaintext
984 lines
1.2 MiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "d5d62d24",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import cv2\n",
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"import matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2799ab25",
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"metadata": {},
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"source": [
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"# Базовая работа с изображением"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "5037aa29",
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"metadata": {},
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"outputs": [],
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"source": [
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"image = cv2.imread('sar_2_color.jpg')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "3e5f356b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x1d1882deb90>"
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]
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},
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"plt.imshow(image)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "37b8f016",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(572, 974, 3)"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"image.shape # h,w,c"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "e4530952",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([12, 12, 12], dtype=uint8)"
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]
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},
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"image[250,250] # b,g,r"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "51aab9ce",
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"metadata": {},
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"outputs": [],
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"source": [
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"# ROI\n",
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"img_roi = image[100:200, 500:700]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"id": "70010d8b",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<matplotlib.image.AxesImage at 0x1d188327220>"
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]
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},
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(img_roi)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"id": "f882dac3",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"b,g,r = cv2.split(image)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 23,
|
||
|
|
"id": "1f89e4b5",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d1883a9390>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(b, cmap = 'gray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 24,
|
||
|
|
"id": "80f48335",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d188781690>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 24,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(g, cmap = 'gray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"id": "14bf6bec",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# alternative approach\n",
|
||
|
|
"b = image[:,:,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 26,
|
||
|
|
"id": "65f6cb65",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"import copy\n",
|
||
|
|
"\n",
|
||
|
|
"image2 = copy.deepcopy(image)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 27,
|
||
|
|
"id": "6e348740",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"image2[50:100,50:100] = [0,0,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 28,
|
||
|
|
"id": "f0af9079",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d1887ea830>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 28,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(image2)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 29,
|
||
|
|
"id": "7b3beafd",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# empty image\n",
|
||
|
|
"image_template = np.zeros(image.shape,np.uint8)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 30,
|
||
|
|
"id": "649438f3",
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": true
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d188bbee60>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 30,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(image_template)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "3c9b56ab",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Конвертация цветовых моделей"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 31,
|
||
|
|
"id": "ddf46c8d",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"array([0, 0, 0], dtype=uint8)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 31,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image_template[0,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 32,
|
||
|
|
"id": "90601bc7",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 33,
|
||
|
|
"id": "4254803d",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"40"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 33,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image_gray[0,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 34,
|
||
|
|
"id": "abb0a164",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(572, 974)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 34,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image_gray.shape"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 35,
|
||
|
|
"id": "f282c88e",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"image_hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 36,
|
||
|
|
"id": "d37c08b1",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(572, 974, 3)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 36,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image_hsv.shape"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 37,
|
||
|
|
"id": "ae9ef2ca",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"array([117, 143, 75], dtype=uint8)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 37,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image_hsv[0,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 38,
|
||
|
|
"id": "d8cdda21",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"array([75, 37, 33], dtype=uint8)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 38,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image[0,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 39,
|
||
|
|
"id": "73fdb374",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"image_lab = cv2.cvtColor(image, cv2.COLOR_BGR2Lab)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 40,
|
||
|
|
"id": "0ed9c8e4",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"array([ 42, 139, 104], dtype=uint8)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 40,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"image_lab[0,0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "e0d7f4f0",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Пороговая фильтрация"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 67,
|
||
|
|
"id": "0b6d5e3f",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"_,thresh1 = cv2.threshold(image_gray,200,255,cv2.THRESH_BINARY)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 68,
|
||
|
|
"id": "6e84b905",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d199a491b0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 68,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(thresh1, cmap='gray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 43,
|
||
|
|
"id": "f5e1453e",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"0"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 43,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"thresh1[thresh1==100].sum()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "396e3b66",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Построение гистограммы"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 44,
|
||
|
|
"id": "4b455e07",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"histSize = 256\n",
|
||
|
|
"histRange = (0, 256)\n",
|
||
|
|
"accumulate = False\n",
|
||
|
|
"\n",
|
||
|
|
"b_hist = cv2.calcHist([b], [0], None, [histSize], histRange, accumulate=accumulate)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 45,
|
||
|
|
"id": "477df536",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"[<matplotlib.lines.Line2D at 0x1d1872a9150>]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 45,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(b_hist)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 46,
|
||
|
|
"id": "92636df5",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"b_hist_cum = b_hist.cumsum()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 47,
|
||
|
|
"id": "1a195130",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"[<matplotlib.lines.Line2D at 0x1d18981cac0>]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 47,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(b_hist_cum)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 49,
|
||
|
|
"id": "e11f8476",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"b_hist_norm = b_hist / (image.shape[0] * image.shape[1])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 50,
|
||
|
|
"id": "ae7a2b79",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"[<matplotlib.lines.Line2D at 0x1d1898b4700>]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 50,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(b_hist_norm)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "aa3739f4",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Сравнение двух изображений"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 53,
|
||
|
|
"id": "b67e4981",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"SSIM: 1.0\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"from skimage.metrics import structural_similarity, mean_squared_error\n",
|
||
|
|
"\n",
|
||
|
|
"(ssim, diff) = structural_similarity(image_gray, image_gray, full=True)\n",
|
||
|
|
"diff = (diff * 255).astype(\"uint8\")\n",
|
||
|
|
"print(\"SSIM: {}\".format(ssim))"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 54,
|
||
|
|
"id": "e130dabe",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d199798df0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 54,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(diff)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 55,
|
||
|
|
"id": "03ab140b",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"0.0"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 55,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"mse = mean_squared_error(image_gray, image_gray)\n",
|
||
|
|
"mse"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"id": "a7c085bc",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Статистические характеристики изображений"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 56,
|
||
|
|
"id": "de9202f2",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"mean = image_gray.mean()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 57,
|
||
|
|
"id": "aaff4206",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"std = image_gray.std()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 58,
|
||
|
|
"id": "248147b1",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"67.41225535245043 52.016191875959635\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"print(mean,std)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 60,
|
||
|
|
"id": "3fbab27e",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"eq_gray = cv2.equalizeHist(image_gray)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 63,
|
||
|
|
"id": "250af16c",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d19993a3e0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 63,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAADnCAYAAADl0RYJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy89olMNAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOz9aYxcaXYdiq6Y53mOjMh5ZpLJoUhWkdWsqavnVre61ep3JQEaLFiALUOCJcD2r/fHgC9gA4LhBz1YkCWr3JK6bakl9awauoo1kSzOTOY8RWZGZETGPGXMw/uRvTZP0qqSr5/73rLAAxSKTEZGxPnO9+299tpr763q9/t4cj25nlxPrifXP6xL/f/0F3hyPbmeXE+uJ9f/+uuJcX9yPbmeXE+uf4DXE+P+5HpyPbmeXP8AryfG/cn15HpyPbn+AV5PjPuT68n15Hpy/QO8nhj3J9eT68n15PoHeP1UjLtKpfqMSqVaValUGyqV6l/+ND7jyfXkenI9uZ5cH36p/lfr3FUqlQbAGoCXAcQB3ATwf/T7/aX/pR/05HpyPbmeXE+uD71+Gsj9AoCNfr+/1e/3WwC+CeBLP4XPeXI9uZ5cT64n14dc2p/Cew4A2FP8PQ7g4uMvUqlU/xjAPwYAnU53zu/3o9frQaPRQK1WQ6VSodvtotPpoNvtwmAwQKfTAQCazSbUajV6vR7UajW63S76/T7UajW0Wi263S7U6iO/1el0oNVq5fV8rU6ng0qlQq/Xg1arRb/fh0ajQafTkf+0Wi20Wi06nQ5UKhVUKhW0Wi1MJpN8r3a7DZ1Oh16vJ3/md1SpVNBoNOj1euj1evL7zWYTAOQ79/t9WK1WtNtteV+NRoNGowGdTod+vy/fudlswmKxoF6vo9PpQK1Ww2AwoNvtyvrxM/l+Op1O3pNrolKpUK1W5c8mkwk2m03uQaPRyPer1+totVpQq9XodDpoNBqPP0tZb64jAPR6Pfl3Roj9fh8qlerYn7k2/B5GoxF6vR6tVgtarRaNRgN6vR5qtRqtVkvuVa1Wo9FooNfrwW63Q61WQ6fTyT3zefMzOp0OjEajfF+dTgej0Sivq9frsuYajUbWrd1uo1aryd60Wq2yVwBArVajVCrJs1LuMYvFAr1ej3a7jXa7Ld9brVajVqvJ+ne73WPPiftCeS/8TH5/tVp97D35mm63C71ef2z9+Tqt9ujI8z25z5vNpvw71wYADAaDPE9+T96zWq2GRqNBrVaTM8u15H9qtRrNZlPWg+t6eHgoe0yv10Oj0ci6ApDPaTQaqFar8Pl8ssdarRZarZZ8P36+2WxGrVZDq9WC1WoFANTrdWg0GrTbbfl/vV6Hy+WS9e10OnLGbDYbyuWyfG+DwXDsXi0Wi7xPtVo9tlbFYlH2usPhQLvdhtlsRr/fl33qcDhQq9VkP/FZ8axqtVq4XC7k83kcHh7CYDBAr9dDq9Wi1+vBaDSKHajX69jf38/2+33f32WIfxrG/X/o6vf7fwDgDwAgHA73f/EXfxE2mw16vR7Dw8O4du0aut0uQqEQrFYrMpkM3G436vU6zGYzms0mbDYbcrkcisUirFYrTCYTVCoVjEajGPlMJoPBwUFUKhVZEI1GA4fDAbvdjnq9Dr1ej2g0iqtXryISicBms0Gj0SCbzSIQCKBUKskDr9Vq8p1SqRS63S5GRkZQKBSwvr4Ou92OmZkZZDIZAMDy8jJmZ2dRLBbRaDQQiURQqVSQSCSgVqsRiUSQTqfR7/fRarXE2ABAJpOB2WyG2WyG0+mEw+FAIBCARqNBPB6H0+mEy+XC9va2HOBUKoVEIoFmswmdTicbuVwuw263IxqNYn9/H9euXcPe3p4caLPZjNHRUWQyGczPz+Ppp5/GzZs34XA44HA4sLy8jEwmg83NTXmGnU7nmNOyWCwAAK1WKw6HrwEgDpUHiQdYpVKJIT88PIRWq8XJkydx4sQJtFotFItFjI6OAgCSySR0Oh2q1SoSiQS2trbQbDbxqU99CmfPnkWxWITdbke1WsXVq1dhsVhgs9lgsVjgdDqh1+sxODiIer0OtVoNr9cLu92OSCSCeDyOmzdvYmhoCM1mE7Ozs8hkMvjud7+LTqeDSCSCfD4PvV6P06dPQ6PRYG9vDzabDUNDQ0gkEshkMigWi6hWq9BoNHjmmWcQiURQrVaRTCYRDoeRSqVgsViQTqdhMplQr9extLSEQqGA2dlZ9Pt9+P1+3L59GzqdDsFgEJFIBJlMBru7uzAajRgbG0Oz2cT+/j6y2SwsFgu0Wi0ikQj29/fh9XqRTCYBACaTCV6vF6lUShy12WyGy+VCt9tFs9mEx+NBqVRCtVqFyWTCM888A61Wi3K5DI/Hg0wmg0ajAa1Wi2AwCJvNJgbn4OAA5XIZFosF4+PjWFlZQbPZRK1Wg9vtxs7ODnZ2dtDv9+HxeOB2u3F4eIh2u41GowGHwwGLxYLz58/D5XLB5XKJo7h+/Tqq1Sq++MUvotlsIpVK4fDwEMFgEDs7OxgdHUWn00E8Hkc8HsfQ0BCi0SiKxSJqtRpeffVVzM7OQqfTwWaz4c///M/hcrnwL/7Fv0Cj0cD9+/fhdrvx1ltvYWtrC5/73Oeg0+kETL7zzjuyjk6nE7/6q78q5+lv/uZv0Ol08IlPfAJOpxPvv/8+7t69C5VKhcnJSVitVni9XlgsFqyvryMQCGB4eBjlchm1Wg3Ly8t45513MDMzI84rHo/j0qVL0Ol0+Na3voVqtYpnn30WNpsN/X4fw8PDCIfDuHfvHmKxGP7Vv/pXOx9mY38axj0BIKr4e+QnP/vQy2g0wuFwYGdnByaTCQAwODgInU4HvV4PnU4nXjGfz6NSqcBsNqNarSKTycBms6Hb7WJ/fx8ejwfBYBB2ux3lchmtVgsejwenTp3C2toa4vE4+v2+HAa73Y5arYadnR1Eo1F0u13k83moVCrYbDbs7+8LItvf3xcUnslk4PV60W63xdAODQ3hwYMH6HQ60Ov1sFgscpir1Sr8fr8g7nq9LhvY4XAgFosJ8vJ6vWg0GnA6nVCr1bIGSvTSbDbxxhtvQKfTwWw2Q6VS4eDgACqVCg6HA91uFzabDUajEY1GA2azGZ1OB+l0GrlcDqlUSj5PpVKJgdHpdFhaWoJGo8GpU6dgt9sRi8Wg0WiQy+UEJRJ104grf9bpdNBut9HtdgWFE3ECkOik3+9LFETkZzKZ0O/3sbGxgWw2i16vh3g8DgCCnhjJNZtNaDQanDhxAuFwGJlMBjs7O/iZn/kZvP7662i322i1Wsjn81hfXwdw5BxOnDiB0dFRBINBGAwGuQe73Y5Tp04hHo9jcHAQWq0WTqcTU1NTKJVKcDgc0Ov1AIB2uw29Xg+32w2NRoNisYitrS1MTExgdHQUW1tbiMfj2NnZwf7+PoLBICwWC+x2O7a3t+F0OmG1WpFMJjEwMICBgQGJKur1OrLZLLrdLpxOJ8rlMprNJgYGBmC1WpHP53FwcIBSqQS1Wg23241AIIDd3V3Y7XaoVCrodDq4XC4kk0m0223YbDZYrVZBpjw7BoMBjUYDMzMzaDQaODw8RL1eR7PZhN1ux/DwsBhUGl2tVoudnR04nU7Mzs4iFAphfX0diURC9unKygpOnDgh30Wv12N9fR25XA56vR7ZbBajo6MoFAriZO/duydGnue3Wq3i5MmTUKlUKJVKcpaCwSACgQBqtRqazSa2t7fh8XgkQnA6nbh+/Tpeeukl9Pt95HI5hMNhPP3004hGo1Cr1XA6nThx4gT+5m/+BkajEXNzc1hfX8fc3BxyuRyCwSDOnj2LVquFjY0NbGxsoFAoIBwOy365evUqRkZG4HA4MDY2hlwuh62tLdy5cwef/vSnUalUoFarMTMzg1arhVgsBpPJhBMnTmB6ehrDw8P40z/9U+zs7GB+fh7Dw8NYXFzEiy++iE9/+tN47bXXsLy8jMuXL6PVaiGVSqHdbsNoNCIUCn2kIf5pGPebACZUKtUIjoz6/wvAL3zUL1QqFTEg5XIZbrdbwqVWq4VyuSyIjMaOXtxiscDhcKBQKAhyVav
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(eq_gray, cmap=\"gray\")\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 64,
|
||
|
|
"id": "7c013a0e",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.image.AxesImage at 0x1d1999ae920>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 64,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.imshow(image_gray, cmap=\"gray\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"id": "6329e214",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# 1. Загрузите изображение в оттенках серого sar_1_gray.jpg. \n",
|
||
|
|
"# 2. постройте гистограмму\n",
|
||
|
|
"# 3. реализуйте алгоритм гамма коррекции с параметром гамма <1, >1.\n",
|
||
|
|
"# 4. Сравните исходное изображение, скорректированное при помощи гамма-фильтра. MSE, SSIM.\n",
|
||
|
|
"# 5. реализуйте алгоритм статистической цветокоррекции на основе статистики eq_gray.\n",
|
||
|
|
"# 6. Протестируйте работу алгоритмов пороговой фильтрации с различными параметрами.\n",
|
||
|
|
"# Для каждого решения - напечатайте результат\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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",
|
||
|
|
"version": "3.10.4"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 5
|
||
|
|
}
|