Newer
Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "b6649867",
"metadata": {},
"outputs": [],
"source": [
"from astropy.io import fits\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import glob\n",
"import cv2\n",
"from PIL import Image\n",
"import copy\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ed76de12",
"metadata": {},
"outputs": [],
"source": [
"ruta_fits = \"RUTA_INPUT_FITS/\"\n",
"ruta_guardar_mascaras_2_clases=\"RUTA_OUTPUT_MASCARAS/\"\n",
"tam_fotos_x=512\n",
"tam_fotos_y=512"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4ee87765",
"metadata": {},
"outputs": [],
"source": [
"if not os.path.exists(ruta_guardar_mascaras_2_clases):\n",
" os.makedirs(ruta_guardar_mascaras_2_clases)"
]
},
{
"cell_type": "markdown",
"id": "187a3d92",
"metadata": {},
"source": [
"## Creamos máscaras de segmentación con 2 clases y de 3 clases"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "62e367b8",
"metadata": {},
"outputs": [],
"source": [
"def get_numero_galaxia(nombre_galaxia:str):\n",
" numero_galaxia = nombre_galaxia.split('.')[0].split('_')[-1]\n",
" return numero_galaxia"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "25dc0528",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"#Leemos las galaxy convolved y las stream convolved\n",
"rutas_stream_convolved = glob.glob(ruta_fits+\"stream_pix_above_surf_bright_limit_*.fits\")\n",
"\n",
"for ruta_stream in rutas_stream_convolved:\n",
" print(ruta_stream)\n",
" numero_galaxia = get_numero_galaxia(ruta_stream)\n",
" print(numero_galaxia)\n",
" \n",
" #Hacemos el mismo proceso para la imagen de la cola de marea\n",
" stream_fits = fits.open(ruta_stream)\n",
" array_imagen_stream_fits = stream_fits[1].data\n",
" mascara_cola = np.zeros((tam_fotos_x,tam_fotos_y))\n",
" mascara_cola[array_imagen_stream_fits!=0] = 1\n",
" #Combinamos las mascaras \n",
" \n",
" #Guardamos la mascara de la cola\n",
" cv2.imwrite(ruta_guardar_mascaras_2_clases+\"mascara_\"+str(numero_galaxia)+\".png\",mascara_cola)\n",
" #Mostramos la mascara\n",
" plt.imshow(mascara_cola,interpolation='none', origin=\"lower\")\n",
" plt.show()"
]
}
],
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}