Upload 5 files (#1)
Browse files- Upload 5 files (d8ff46df6e40fd3ad80a0e90509b6ff15a0900fc)
- Pipfile +17 -0
- Pipfile.lock +525 -0
- image.png +0 -0
- remove.py +160 -0
- style.css +11 -0
Pipfile
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[[source]]
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url = "https://pypi.org/simple"
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verify_ssl = true
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name = "pypi"
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[packages]
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pandas = "*"
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pydub = "*"
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beautifulsoup4 = "*"
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yfinance = "*"
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scikit-learn = "*"
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[dev-packages]
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[requires]
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python_version = "3.12"
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python_full_version = "3.12.0"
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Pipfile.lock
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@@ -0,0 +1,525 @@
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{
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"_meta": {
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"hash": {
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"sha256": "fca73292f8f26d1b48931017796e5e119d0cb9c23608e3208de3b208d23c65cb"
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},
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"pipfile-spec": 6,
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"python_full_version": "3.12.0",
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"python_version": "3.12"
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"sources": [
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{
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"name": "pypi",
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"url": "https://pypi.org/simple",
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"verify_ssl": true
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"default": {
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"index": "pypi",
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"sha256:ee410e6de8f88fd5cf6eadd73c135020bfbbbdfcd0f6162c36a7638a1ea8cc65",
|
462 |
+
"sha256:f313b39a7e94f296025e3cffc2c567618174c0b1dde173960cf23808f9fae4be",
|
463 |
+
"sha256:f3cd9e7b3c2c1ec26364856f9fbe78695fe631150f94cd1c22228456404cf1ec"
|
464 |
+
],
|
465 |
+
"markers": "python_version >= '3.9'",
|
466 |
+
"version": "==1.11.4"
|
467 |
+
},
|
468 |
+
"six": {
|
469 |
+
"hashes": [
|
470 |
+
"sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926",
|
471 |
+
"sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"
|
472 |
+
],
|
473 |
+
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
|
474 |
+
"version": "==1.16.0"
|
475 |
+
},
|
476 |
+
"soupsieve": {
|
477 |
+
"hashes": [
|
478 |
+
"sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690",
|
479 |
+
"sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7"
|
480 |
+
],
|
481 |
+
"markers": "python_version >= '3.8'",
|
482 |
+
"version": "==2.5"
|
483 |
+
},
|
484 |
+
"threadpoolctl": {
|
485 |
+
"hashes": [
|
486 |
+
"sha256:2b7818516e423bdaebb97c723f86a7c6b0a83d3f3b0970328d66f4d9104dc032",
|
487 |
+
"sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"
|
488 |
+
],
|
489 |
+
"markers": "python_version >= '3.8'",
|
490 |
+
"version": "==3.2.0"
|
491 |
+
},
|
492 |
+
"tzdata": {
|
493 |
+
"hashes": [
|
494 |
+
"sha256:aa3ace4329eeacda5b7beb7ea08ece826c28d761cda36e747cfbf97996d39bf3",
|
495 |
+
"sha256:dd54c94f294765522c77399649b4fefd95522479a664a0cec87f41bebc6148c9"
|
496 |
+
],
|
497 |
+
"markers": "python_version >= '2'",
|
498 |
+
"version": "==2023.4"
|
499 |
+
},
|
500 |
+
"urllib3": {
|
501 |
+
"hashes": [
|
502 |
+
"sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3",
|
503 |
+
"sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"
|
504 |
+
],
|
505 |
+
"markers": "python_version >= '3.8'",
|
506 |
+
"version": "==2.1.0"
|
507 |
+
},
|
508 |
+
"webencodings": {
|
509 |
+
"hashes": [
|
510 |
+
"sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78",
|
511 |
+
"sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"
|
512 |
+
],
|
513 |
+
"version": "==0.5.1"
|
514 |
+
},
|
515 |
+
"yfinance": {
|
516 |
+
"hashes": [
|
517 |
+
"sha256:bfd5102cc9e5aa259c26b86fb53c2abe9e05ff63d387c03adf0b4ff2f6f2375a",
|
518 |
+
"sha256:f3d15cbf06fadd06c607520f70c54cbae4560a99675307ee2383d000232614f8"
|
519 |
+
],
|
520 |
+
"index": "pypi",
|
521 |
+
"version": "==0.2.35"
|
522 |
+
}
|
523 |
+
},
|
524 |
+
"develop": {}
|
525 |
+
}
|
image.png
ADDED
![]() |
remove.py
ADDED
@@ -0,0 +1,160 @@
|
|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import decimal
|
2 |
+
import os.path
|
3 |
+
from io import BytesIO
|
4 |
+
from os import path
|
5 |
+
from pathlib import Path
|
6 |
+
|
7 |
+
import numpy.random
|
8 |
+
from PIL.ImageFilter import *
|
9 |
+
from rembg import remove
|
10 |
+
import streamlit as s
|
11 |
+
from PIL import Image, ImageColor, ImageFilter
|
12 |
+
from aspose.imaging import RasterImage
|
13 |
+
import aspose.pycore as aspycore
|
14 |
+
|
15 |
+
s.set_page_config(page_title="BACKGROUND", page_icon=":book:", layout="centered", initial_sidebar_state="auto")
|
16 |
+
with open("style.css") as file_style:
|
17 |
+
s.markdown(f"<style>{file_style.read()}</style>", unsafe_allow_html=True)
|
18 |
+
|
19 |
+
s.write("<h1 style='color:yellow;'>UNE NOUVELLE MANIERE DE MANUPULER LES IMAGES</h1>", unsafe_allow_html=True)
|
20 |
+
s.write("###### Vous avez marre de toujours utiliser Photoshop :dog: ! Mais oui, il fait ramer votre ordinateur. ")
|
21 |
+
s.write("###### Mais la solution, elle est là ! BACKGROUND vous ouvre ses porte.")
|
22 |
+
s.write("### Enlever l'arrière-plan de l'image")
|
23 |
+
s.sidebar.write("# :snake: Background :snake:")
|
24 |
+
|
25 |
+
col1, col2 = s.columns(2)
|
26 |
+
|
27 |
+
bordure = s.sidebar.number_input("Améliorer la bordure", min_value=0, max_value=400, value=220, step=5)
|
28 |
+
fond = s.sidebar.slider("Améliorer l'arrière-plan", min_value=0, max_value=100, value=15)
|
29 |
+
row1 = s.sidebar.container(border=True)
|
30 |
+
check = row1.checkbox("Activer le masque", value=False)
|
31 |
+
contoure_leger = row1.checkbox("Contour léger", value=False)
|
32 |
+
select_img_filtre = row1.selectbox("Filtres", options=(
|
33 |
+
"Selectionner un filtre", "Flou panoramic", "Nettété", "Flou Gaussien", "Masquage flou"))
|
34 |
+
|
35 |
+
# On charge l'image
|
36 |
+
image_upload = s.file_uploader("Choississez une image", type=["png", "jpg", "jpeg"], accept_multiple_files=False)
|
37 |
+
|
38 |
+
|
39 |
+
def convert_img(image):
|
40 |
+
buf = BytesIO()
|
41 |
+
image.save(buf, format="PNG")
|
42 |
+
byte_img = buf.getvalue()
|
43 |
+
return byte_img
|
44 |
+
|
45 |
+
|
46 |
+
def fix_image(image):
|
47 |
+
image = Image.open(image)
|
48 |
+
|
49 |
+
# Ajout des éléments dans la colonne 1
|
50 |
+
col1.write("### Image originale")
|
51 |
+
col1.image(image)
|
52 |
+
# Traiter l'image
|
53 |
+
fixed = remove(image, alpha_matting=False, only_mask=check, alpha_matting_background_threshold=fond,
|
54 |
+
alpha_matting_foreground_threshold=bordure, post_process_mask=contoure_leger)
|
55 |
+
|
56 |
+
# Affichage de l'image détourrée
|
57 |
+
new_fixed = fixed
|
58 |
+
if select_img_filtre != "Selectionner un filtre":
|
59 |
+
|
60 |
+
if select_img_filtre == "Flou panoramic":
|
61 |
+
blur_value = row1._number_input("Intensité du flou panaoramic :", min_value=0.0, max_value=100.0,
|
62 |
+
value=10.0, step=5.0)
|
63 |
+
fixed = convert_img(fixed.filter(GaussianBlur(radius=blur_value)))
|
64 |
+
|
65 |
+
print("Blur")
|
66 |
+
|
67 |
+
elif select_img_filtre == "Nettété":
|
68 |
+
fixed = convert_img(fixed.filter(DETAIL))
|
69 |
+
print("Détail")
|
70 |
+
|
71 |
+
elif select_img_filtre == "Flou Gaussien":
|
72 |
+
blur_value = row1._number_input("Intensité du flou gaussien :", min_value=0.0, max_value=100.0,
|
73 |
+
value=20.0, step=2.0)
|
74 |
+
fixed = convert_img(fixed.filter(BoxBlur(radius=blur_value)))
|
75 |
+
|
76 |
+
|
77 |
+
|
78 |
+
elif select_img_filtre == "Masquage flou":
|
79 |
+
blur_value = row1._number_input("Niveau du flou :", min_value=0, max_value=10,
|
80 |
+
value=5, step=1)
|
81 |
+
|
82 |
+
# le seuil contrôle le changement de luminosité minimum qui sera accentué
|
83 |
+
lumiere_value = row1._number_input("Seuil de la luminosité:", min_value=0, max_value=30,
|
84 |
+
value=3, step=1)
|
85 |
+
# pourcentage de rayon de flou
|
86 |
+
per_value = row1._number_input("Pourcentage de l'effet :", min_value=0, max_value=500,
|
87 |
+
value=100, step=5)
|
88 |
+
|
89 |
+
def hex_to_rgb(hex):
|
90 |
+
"""
|
91 |
+
Utilisez une compréhension de liste en combinaison avec int()une notation de tranche de liste pour obtenir les composants RVB de la chaîne hexadécimale.
|
92 |
+
Utilisez tuple()pour convertir la liste résultante en tuple.
|
93 |
+
:param hex:
|
94 |
+
:return:
|
95 |
+
"""
|
96 |
+
return tuple(int(hex[i:i + 2], 16) for i in (0, 2, 4))
|
97 |
+
|
98 |
+
fixed = convert_img(
|
99 |
+
fixed.filter(UnsharpMask(radius=blur_value, percent=per_value, threshold=lumiere_value)))
|
100 |
+
|
101 |
+
if select_img_filtre == "Flou panoramic":
|
102 |
+
col2.write("### Image détourée avec Flou panoramic")
|
103 |
+
|
104 |
+
col2.image(fixed)
|
105 |
+
s.sidebar.markdown("\n")
|
106 |
+
s.sidebar.download_button("Télécharger l'image", fixed, mime="image/png",
|
107 |
+
file_name="image.png")
|
108 |
+
|
109 |
+
elif select_img_filtre == "Nettété":
|
110 |
+
col2.write("### Image détourée nette")
|
111 |
+
|
112 |
+
col2.image(fixed)
|
113 |
+
s.sidebar.markdown("\n")
|
114 |
+
s.sidebar.download_button("Télécharger l'image", fixed, mime="image/png",
|
115 |
+
file_name="image.png")
|
116 |
+
elif select_img_filtre == "Flou Gaussien":
|
117 |
+
col2.write("### Image détourée avec Flou Gaussien")
|
118 |
+
|
119 |
+
col2.image(fixed)
|
120 |
+
s.sidebar.markdown("\n")
|
121 |
+
s.sidebar.download_button("Télécharger l'image", fixed, mime="image/png",
|
122 |
+
file_name="image.png")
|
123 |
+
elif select_img_filtre == "Masquage flou":
|
124 |
+
col2.write("### Image détourée - Autres Effets")
|
125 |
+
col2.image(fixed)
|
126 |
+
s.sidebar.markdown("\n")
|
127 |
+
s.sidebar.info(
|
128 |
+
"Rendre les images plus claires et plus claires et spectaculaires en augmentant le contraste et en réduisant le bruit.")
|
129 |
+
|
130 |
+
s.sidebar.download_button("Télécharger l'image", fixed, mime="image/png",
|
131 |
+
file_name="image.png")
|
132 |
+
|
133 |
+
else:
|
134 |
+
col2.write("### Image détourée")
|
135 |
+
|
136 |
+
col2.image(fixed)
|
137 |
+
s.sidebar.markdown("\n")
|
138 |
+
s.sidebar.download_button("Télécharger l'image", fixed.tobytes(), mime="image/png",
|
139 |
+
file_name="image.png")
|
140 |
+
# Information sur l'image
|
141 |
+
s.markdown(f"#### Informations sur l'image :")
|
142 |
+
s.markdown("\n")
|
143 |
+
if select_img_filtre == "Selectionner un filtre":
|
144 |
+
s.markdown(
|
145 |
+
f"<p> Taille de l'image : {image.width} x {image.height}</p> <p>Mode avant : {image.mode} - Mode après : {image.mode}</p>"
|
146 |
+
f"<p>Format de l'image : {image.format}</p>"
|
147 |
+
f"<p>Format ISO : {image.format_description}</p>", unsafe_allow_html=True)
|
148 |
+
s.markdown(f"<p>Dimension bordure : {fixed.getbbox()}</p>", unsafe_allow_html=True)
|
149 |
+
|
150 |
+
else:
|
151 |
+
s.markdown(
|
152 |
+
f"<p> Taille de l'image : {image.width} x {image.height}</p> <p>Mode avant : {image.mode}</p>"
|
153 |
+
f"<p>Format de l'image : {image.format}</p>"
|
154 |
+
f"<p>Format ISO : {image.format_description}</p>", unsafe_allow_html=True)
|
155 |
+
|
156 |
+
|
157 |
+
if image_upload is not None:
|
158 |
+
fix_image(image_upload)
|
159 |
+
else:
|
160 |
+
s.write("##### En attente d'une image uploadée !")
|
style.css
ADDED
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
.st-emotion-cache-6qob1r
|
2 |
+
{
|
3 |
+
color:yellow;
|
4 |
+
background-color:#8E0049 ;
|
5 |
+
}
|
6 |
+
|
7 |
+
.st-emotion-cache-k7vsyb h1
|
8 |
+
{
|
9 |
+
text-align:center;
|
10 |
+
font-family: Microsoft YaHei UI light ;
|
11 |
+
}
|