Delete app.py
Browse files
app.py
DELETED
@@ -1,373 +0,0 @@
|
|
1 |
-
#Imports
|
2 |
-
import gradio as gr
|
3 |
-
from PIL import Image, UnidentifiedImageError
|
4 |
-
from gtts import gTTS
|
5 |
-
import requests
|
6 |
-
import re
|
7 |
-
import torch
|
8 |
-
from transformers import CLIPProcessor, CLIPModel, pipeline
|
9 |
-
from sentence_transformers import SentenceTransformer, util
|
10 |
-
from langdetect import detect
|
11 |
-
from io import BytesIO
|
12 |
-
import pandas as pd
|
13 |
-
import numpy as np
|
14 |
-
import soundfile as sf
|
15 |
-
import os
|
16 |
-
import subprocess
|
17 |
-
|
18 |
-
# Run the setup script to install espeak-ng
|
19 |
-
subprocess.run(['bash', 'setup.sh'], check=True)
|
20 |
-
|
21 |
-
|
22 |
-
# DataFrame with information about the Paintings as image url, Title, description , stroy
|
23 |
-
|
24 |
-
data = {
|
25 |
-
"image_url": [
|
26 |
-
"https://s.turbifycdn.com/aah/gallerydirectart/vincent-van-gogh-estate-signed-limited-edition-giclee-starry-night-47.png", # Starry Night
|
27 |
-
"https://cdn.mos.cms.futurecdn.net/xRqbwS4odpkSQscn3jHECh-1200-80.jpg", # Mona Lisa
|
28 |
-
"https://upload.wikimedia.org/wikipedia/en/d/dd/The_Persistence_of_Memory.jpg", # The Persistence of Memory
|
29 |
-
"https://static.wixstatic.com/media/1071a8_cf1930f883e043e28d03d5a26a5960ef~mv2.jpg/v1/fill/w_568,h_718,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/1071a8_cf1930f883e043e28d03d5a26a5960ef~mv2.jpg", # The Scream
|
30 |
-
"https://images.artbrokerage.com/artthumb/magritte_158194_1/625x559/Rene_Magritte_Le_Fils_De_lhomme_the_Son_of_Man_1973.jpg", # The Son of Man
|
31 |
-
"https://www.artic.edu/iiif/2/25c31d8d-21a4-9ea1-1d73-6a2eca4dda7e/full/843,/0/default.jpg", # The Bedroom
|
32 |
-
"https://images.desenio.com/zoom/17047_1.jpg", # Girl with a Pearl Earring
|
33 |
-
"https://www.hastingsindependentpress.co.uk/wp-content/uploads/2021/03/Whistlers-Mother.jpg", # Whistler’s Mother
|
34 |
-
"https://live.staticflickr.com/7173/6713746433_652c3d9d4e_c.jpg" # The Basket of Apples
|
35 |
-
],
|
36 |
-
"Title": [
|
37 |
-
"Starry Night", "Mona Lisa", "The Persistence of Memory", "The Scream",
|
38 |
-
"The Son of Man", "The Bedroom",
|
39 |
-
"Girl with a Pearl Earring", "Whistler’s Mother", "The Basket of Apples"
|
40 |
-
],
|
41 |
-
"Description": [
|
42 |
-
# Starry Night
|
43 |
-
("Starry Night by Vincent van Gogh, painted in 1889, is one of the most famous works of art in the world. "
|
44 |
-
"It depicts a swirling night sky filled with stars over a small town. The painting uses vibrant colors like blue and yellow, "
|
45 |
-
"with exaggerated swirling patterns that create a dreamlike, almost chaotic feeling."),
|
46 |
-
|
47 |
-
# Mona Lisa
|
48 |
-
("The Mona Lisa by Leonardo da Vinci, painted between 1503 and 1506, is a portrait of a woman with a subtle, enigmatic smile. "
|
49 |
-
"The use of muted colors, including soft browns, greens, and black, emphasizes the serene and mysterious nature of the subject. "
|
50 |
-
"It is one of the most studied and recognized works of art in history."),
|
51 |
-
|
52 |
-
# The Persistence of Memory
|
53 |
-
("The Persistence of Memory, created by Salvador Dalí in 1931, features melting clocks draped over a surreal landscape. "
|
54 |
-
"The painting, primarily in soft shades of brown, blue, and yellow, explores themes of time and memory. The abstract shapes "
|
55 |
-
"and dreamlike atmosphere make it one of Dalí’s most famous surrealist works."),
|
56 |
-
|
57 |
-
# The Scream
|
58 |
-
("The Scream by Edvard Munch, painted in 1893, is one of the most iconic images in modern art. "
|
59 |
-
"It depicts a figure standing on a bridge, clutching their face in agony, as a blood-red sky swirls behind them. "
|
60 |
-
"The painting uses bold reds, oranges, and blues to evoke a sense of horror and existential despair."),
|
61 |
-
|
62 |
-
# The Son of Man
|
63 |
-
("The Son of Man by René Magritte, painted in 1964, is a surrealist self-portrait of the artist. "
|
64 |
-
"It depicts a man in a bowler hat and suit, with his face obscured by a floating green apple. "
|
65 |
-
"The background features a cloudy sky and a low wall, contributing to the dreamlike atmosphere. The painting is rich in symbolism, "
|
66 |
-
"exploring themes of identity, concealment, and perception."),
|
67 |
-
|
68 |
-
# The Bedroom
|
69 |
-
("The Bedroom by Vincent van Gogh, painted in 1888, depicts the artist’s simple bedroom in Arles, France. "
|
70 |
-
"The painting uses bold, contrasting colors—yellow, red, and blue—to create a vibrant, almost childlike view of the space. "
|
71 |
-
"Van Gogh painted this scene three times, each version representing his sense of comfort and sanctuary in his personal space."),
|
72 |
-
|
73 |
-
# Girl with a Pearl Earring
|
74 |
-
("Girl with a Pearl Earring by Johannes Vermeer, painted in 1665, is often referred to as the 'Mona Lisa of the North.' "
|
75 |
-
"The painting shows a young girl looking over her shoulder, wearing a large pearl earring. The use of light and shadow, "
|
76 |
-
"combined with soft colors like blue and yellow, creates a lifelike, intimate portrait."),
|
77 |
-
|
78 |
-
# Whistler’s Mother
|
79 |
-
("Whistler’s Mother by James McNeill Whistler, painted in 1871, is a portrait of the artist’s mother seated in profile. "
|
80 |
-
"The painting uses muted tones of black, gray, and brown, reflecting the simplicity and dignity of the subject. "
|
81 |
-
"It has become an icon of motherhood and restraint."),
|
82 |
-
|
83 |
-
# The Basket of Apples
|
84 |
-
("The Basket of Apples by Paul Cézanne, painted around 1895, is a still life that challenges traditional perspectives. "
|
85 |
-
"The painting shows a table with a basket of apples, a bottle, and bread. The use of soft colors, including browns, reds, and greens, "
|
86 |
-
"along with the tilted angles, makes the objects seem to float, blurring the line between realism and abstraction.")
|
87 |
-
],
|
88 |
-
"Story": [
|
89 |
-
# Starry Night
|
90 |
-
("Vincent van Gogh painted 'Starry Night' while in a mental asylum in Saint-Rémy-de-Provence, France. "
|
91 |
-
"It was created from memory and imagination, rather than a direct view from his window. The swirling patterns "
|
92 |
-
"are thought to represent his emotional turbulence at the time. The painting is celebrated for its bold brushstrokes "
|
93 |
-
"and imaginative use of color, representing the tension between beauty and chaos in the natural world."),
|
94 |
-
|
95 |
-
# Mona Lisa
|
96 |
-
("'Mona Lisa' was painted by Leonardo da Vinci during the Renaissance period. The subject of the painting, "
|
97 |
-
"believed to be Lisa Gherardini, is famed for her mysterious smile. The painting's sfumato technique, blending "
|
98 |
-
"soft transitions between light and shadow, creates a lifelike, three-dimensional appearance. The Mona Lisa has inspired "
|
99 |
-
"countless studies and interpretations over the centuries, and its theft in 1911 only increased its mystique."),
|
100 |
-
|
101 |
-
# The Persistence of Memory
|
102 |
-
("Salvador Dalí's 'The Persistence of Memory' is a surrealist masterpiece that reflects the fluidity of time and memory. "
|
103 |
-
"The melting clocks draped over the landscape suggest the passage of time becoming meaningless. The inspiration for the painting "
|
104 |
-
"came from a melting camembert cheese. Dalí’s fascination with dream states and Freud's theories of the unconscious mind "
|
105 |
-
"are evident in this strange, dreamlike scene."),
|
106 |
-
|
107 |
-
# The Scream
|
108 |
-
("'The Scream' by Edvard Munch is a vivid expression of anxiety and existential dread. Munch was inspired to create the work "
|
109 |
-
"after a walk during which he felt the 'great scream' of nature overwhelm him. The distorted figure and fiery red sky reflect "
|
110 |
-
"Munch’s inner turmoil. The painting has become an iconic representation of human anxiety and has been widely referenced in pop culture."),
|
111 |
-
|
112 |
-
# The Son of Man
|
113 |
-
("René Magritte’s 'The Son of Man' is a quintessential example of surrealism, blending reality and fantasy. "
|
114 |
-
"The painting is a self-portrait with Magritte’s face hidden by a hovering green apple, symbolizing the tension between what is visible "
|
115 |
-
"and what is hidden. The painting has been widely interpreted as a statement on identity and the nature of perception."),
|
116 |
-
|
117 |
-
# The Bedroom
|
118 |
-
("'The Bedroom' by Vincent van Gogh is a reflection of the artist’s longing for stability and tranquility. "
|
119 |
-
"The painting was created during one of the few peaceful periods in van Gogh’s turbulent life, and the vibrant colors convey "
|
120 |
-
"his emotions at the time. The bold, contrasting colors and exaggerated perspective make the simple room appear almost alive."),
|
121 |
-
|
122 |
-
# Girl with a Pearl Earring
|
123 |
-
("'Girl with a Pearl Earring' by Johannes Vermeer is one of the most enigmatic portraits in Western art. Known for its simplicity and elegance, "
|
124 |
-
"the painting captures a fleeting moment of connection between the viewer and the subject. The girl’s mysterious gaze and the radiant light "
|
125 |
-
"on her face have captivated audiences for centuries."),
|
126 |
-
|
127 |
-
# Whistler’s Mother
|
128 |
-
("James McNeill Whistler’s 'Arrangement in Grey and Black No. 1,' more commonly known as 'Whistler’s Mother,' is a stark, dignified portrait "
|
129 |
-
"of the artist’s mother. The painting is renowned for its minimalist composition and restrained use of color. Its iconic status grew after "
|
130 |
-
"its display at the Musée d'Orsay in Paris, becoming a symbol of maternal devotion and calm."),
|
131 |
-
|
132 |
-
# The Basket of Apples
|
133 |
-
("Paul Cézanne’s 'The Basket of Apples' is a revolutionary work that defies the traditional rules of perspective. By tilting objects at different angles, "
|
134 |
-
"Cézanne challenges the viewer’s perception of space and reality. This still life is often cited as a precursor to Cubism, and its soft color palette "
|
135 |
-
"creates a serene yet dynamic composition.")
|
136 |
-
]
|
137 |
-
}
|
138 |
-
|
139 |
-
|
140 |
-
df = pd.DataFrame(data)
|
141 |
-
|
142 |
-
# Load models
|
143 |
-
|
144 |
-
# Determine if a GPU (CUDA) is available
|
145 |
-
device = "cuda" if torch.cuda.is_available() else "cpu"
|
146 |
-
|
147 |
-
# TTS model
|
148 |
-
narrator = pipeline("text-to-speech", model="kakao-enterprise/vits-ljs", device=device)
|
149 |
-
|
150 |
-
# Load the CLIP model and processor
|
151 |
-
model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32").to(device)
|
152 |
-
processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
|
153 |
-
|
154 |
-
# Load the semantic similarity model for description search
|
155 |
-
semantic_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2', device=device)
|
156 |
-
|
157 |
-
# Load the translation models for Arabic to English and English to Arabic translations
|
158 |
-
translator_ar_to_en = pipeline("translation_ar_to_en", model="Helsinki-NLP/opus-mt-ar-en", device=0 if device == "cuda" else -1)
|
159 |
-
translator_en_to_ar = pipeline("translation_en_to_arabic", model="Helsinki-NLP/opus-mt-en-ar", device=0 if device == "cuda" else -1)
|
160 |
-
|
161 |
-
# Function to Convert the text to Speech in Ensglish
|
162 |
-
def text_to_speech_english(story_text):
|
163 |
-
|
164 |
-
audio_output = narrator(story_text)
|
165 |
-
|
166 |
-
# Extract audio and sampling rate from the output
|
167 |
-
audio = np.squeeze(audio_output['audio'])
|
168 |
-
sampling_rate = audio_output['sampling_rate']
|
169 |
-
|
170 |
-
# Save the output as a WAV file using soundfile
|
171 |
-
sf.write("story_english.wav", audio, sampling_rate)
|
172 |
-
|
173 |
-
return "story_english.wav"
|
174 |
-
|
175 |
-
# Function to Convert the text to Speech in Arabic using gTTS
|
176 |
-
def text_to_speech_arabic(story_text):
|
177 |
-
tts = gTTS(text=story_text, lang='ar')
|
178 |
-
tts.save("story_arabic.mp3")
|
179 |
-
return "story_arabic.mp3"
|
180 |
-
|
181 |
-
# Function to translate the full story in chunks
|
182 |
-
def translate_story_to_arabic(story_text):
|
183 |
-
sentences = re.split(r'(?<=[.!؟])\s+', story_text) # ٍSplit the story to list of sentences to translate
|
184 |
-
translated_sentences = []
|
185 |
-
|
186 |
-
for sentence in sentences: # For each sentence translate to arabic and append to the list
|
187 |
-
translation = translator_en_to_ar(sentence)[0]['translation_text']
|
188 |
-
translated_sentences.append(translation)
|
189 |
-
|
190 |
-
return ' '.join(translated_sentences) # Return the translated sentences list elements as one String
|
191 |
-
|
192 |
-
# Function to check if the image URL is valid and fetches the image
|
193 |
-
def fetch_image_from_url(url):
|
194 |
-
try:
|
195 |
-
response = requests.get(url, stream=True)
|
196 |
-
response.raise_for_status() # Check if the request was successful
|
197 |
-
return Image.open(BytesIO(response.content)) # Return the image if valid
|
198 |
-
except Exception as e:
|
199 |
-
print(f"Error fetching image from {url}: {str(e)}")
|
200 |
-
return None
|
201 |
-
|
202 |
-
# Process the result where result is shown base on selected language
|
203 |
-
def process_best_match(best_match, language):
|
204 |
-
best_image_url = best_match["image_url"]
|
205 |
-
best_story = best_match["Story"]
|
206 |
-
|
207 |
-
# Translate to Arabic if the language is Arabic
|
208 |
-
if language == "Arabic":
|
209 |
-
best_story_translated = translate_story_to_arabic(best_story)
|
210 |
-
info_html = f"<div dir='rtl' style='font-size: 18px; color: white; font-family: Arial, sans-serif;'>{best_story_translated}</div>"
|
211 |
-
audio_file = text_to_speech_arabic(best_story_translated)
|
212 |
-
return best_image_url, info_html, audio_file
|
213 |
-
|
214 |
-
# Otherwise, use English
|
215 |
-
info_html = f"<div style='font-size: 18px; color: white;'>{best_story}</div>"
|
216 |
-
audio_file = text_to_speech_english(best_story)
|
217 |
-
return best_image_url, info_html, audio_file
|
218 |
-
|
219 |
-
# Function to match the uploaded image with the DataFrame to retrive the image of painting from the Datafram and it story in text and audio
|
220 |
-
def compare_images(image, language):
|
221 |
-
try:
|
222 |
-
inputs = processor(images=image, return_tensors="pt")
|
223 |
-
image_features = model.get_image_features(**inputs)
|
224 |
-
|
225 |
-
best_score = -2.0
|
226 |
-
best_match_idx = None
|
227 |
-
|
228 |
-
for idx, image_url in enumerate(df['image_url']):
|
229 |
-
db_image = fetch_image_from_url(image_url)
|
230 |
-
if db_image is None:
|
231 |
-
continue
|
232 |
-
|
233 |
-
try:
|
234 |
-
db_inputs = processor(images=db_image, return_tensors="pt")
|
235 |
-
db_image_features = model.get_image_features(**db_inputs)
|
236 |
-
|
237 |
-
similarity = torch.nn.functional.cosine_similarity(image_features, db_image_features).item()
|
238 |
-
if similarity > best_score:
|
239 |
-
best_score = similarity
|
240 |
-
best_match_idx = idx
|
241 |
-
except UnidentifiedImageError:
|
242 |
-
continue
|
243 |
-
|
244 |
-
if best_match_idx is None:
|
245 |
-
return None, "Error: No valid image match found in the database.", None
|
246 |
-
|
247 |
-
best_match = df.iloc[best_match_idx]
|
248 |
-
return process_best_match(best_match, language)
|
249 |
-
|
250 |
-
except UnidentifiedImageError:
|
251 |
-
return None, "Error: The uploaded file is not a valid image.", None
|
252 |
-
except Exception as e:
|
253 |
-
return None, f"Error: {str(e)}", None
|
254 |
-
|
255 |
-
# Function to compare user input with descriptions in the DataFrame and return the best match Painting as image of painting with text and audio story of painting
|
256 |
-
def compare_description(input_text):
|
257 |
-
try:
|
258 |
-
language = detect(input_text) #detect the langauge of input
|
259 |
-
if language == 'ar':
|
260 |
-
input_text = translator_ar_to_en(input_text)[0]['translation_text']
|
261 |
-
|
262 |
-
input_embedding = semantic_model.encode(input_text, convert_to_tensor=True)
|
263 |
-
df_embeddings = semantic_model.encode(df["Description"].tolist(), convert_to_tensor=True)
|
264 |
-
|
265 |
-
similarities = util.pytorch_cos_sim(input_embedding, df_embeddings).squeeze()
|
266 |
-
best_match_idx = torch.argmax(similarities).item()
|
267 |
-
best_match = df.iloc[best_match_idx]
|
268 |
-
|
269 |
-
return process_best_match(best_match, language)
|
270 |
-
|
271 |
-
except Exception as e:
|
272 |
-
return None, f"Error: {str(e)}", None
|
273 |
-
|
274 |
-
# Custom CSS for Styling the Gradio
|
275 |
-
|
276 |
-
custom_css = """
|
277 |
-
.gradio-container {
|
278 |
-
background-image: url('https://images.squarespace-cdn.com/content/v1/587ee1eab3db2b428f68d221/1626734192415-LI75A3LVVFMJD5TVZ3HR/Gallery+2.jpg');
|
279 |
-
background-size: cover;
|
280 |
-
background-position: center;
|
281 |
-
background-repeat: no-repeat;
|
282 |
-
color: #333333;
|
283 |
-
font-family: 'Arial', sans-serif;
|
284 |
-
}
|
285 |
-
|
286 |
-
h1, #title, #description {
|
287 |
-
color: white !important;
|
288 |
-
}
|
289 |
-
|
290 |
-
#upload-text, #description-search-text {
|
291 |
-
color: white !important;
|
292 |
-
}
|
293 |
-
|
294 |
-
label, .gr-label {
|
295 |
-
color: #333333 !important;
|
296 |
-
}
|
297 |
-
|
298 |
-
button.primary {
|
299 |
-
background-color: #6A5ACD;
|
300 |
-
color: black;
|
301 |
-
border-radius: 10px;
|
302 |
-
padding: 10px;
|
303 |
-
margin: 5px;
|
304 |
-
font-size: 18px;
|
305 |
-
border: none;
|
306 |
-
transition: background-color 0.3s;
|
307 |
-
}
|
308 |
-
|
309 |
-
button.primary:hover {
|
310 |
-
background-color: #836FFF;
|
311 |
-
}
|
312 |
-
|
313 |
-
#image_output, #search_image_output {
|
314 |
-
border: 3px solid white;
|
315 |
-
border-radius: 10px;
|
316 |
-
}
|
317 |
-
|
318 |
-
/* Specifically targeting the example buttons */
|
319 |
-
.gr-examples button {
|
320 |
-
color: white !important;
|
321 |
-
background-color: transparent !important; /* Make the background blend in with the overall theme */
|
322 |
-
border: 1px solid white; /* Add a border if you want to highlight it */
|
323 |
-
}
|
324 |
-
"""
|
325 |
-
|
326 |
-
image_upload_examples = [
|
327 |
-
["https://pbs.twimg.com/media/DgAnD-FUcAAr3NT?format=jpg", "English"],
|
328 |
-
["https://pbs.twimg.com/media/DgAnD-FUcAAr3NT?format=jpg", "Arabic"]
|
329 |
-
]
|
330 |
-
|
331 |
-
# Sample Examples for the "Description Search" tab
|
332 |
-
description_search_examples = [
|
333 |
-
["A painting of a swirling night sky over a town.", "English"],
|
334 |
-
["امرأة بابتسامة غامضة.", "Arabic"]
|
335 |
-
]
|
336 |
-
|
337 |
-
# Gradio interface with two tabs: "Image Upload" and "Description Search"
|
338 |
-
# Image Upload tab to get the Painting story by uploding an image
|
339 |
-
# Description Search tab is by getting Painting stroy by descriping the painting
|
340 |
-
|
341 |
-
with gr.Blocks(css=custom_css) as demo:
|
342 |
-
gr.Markdown("<h1 id='title'>Welcome to the Virtual Art Museum</h1>")
|
343 |
-
gr.Markdown("<p id='description'>Explore the most famous artworks. Upload an image or enter a description to learn about the story behind each piece.</p>")
|
344 |
-
|
345 |
-
with gr.Tab("Image Search"):
|
346 |
-
gr.Markdown("<h2 id='upload-text'>Upload Art to Recognize and Hear the Story Behind It</h2>")
|
347 |
-
|
348 |
-
image_input = gr.Image(type="pil", label="Upload an image of an art piece")
|
349 |
-
language_selector = gr.Radio(choices=["English", "Arabic"], label="Select Language for Story Narration", value="English")
|
350 |
-
recognize_button = gr.Button("Search")
|
351 |
-
|
352 |
-
image_output = gr.Image(label="Matched Art Piece", elem_id="image_output")
|
353 |
-
description_output = gr.HTML(label="Art Piece Information")
|
354 |
-
audio_output = gr.Audio(label="Narration of the Story")
|
355 |
-
|
356 |
-
recognize_button.click(compare_images, inputs=[image_input, language_selector], outputs=[image_output, description_output, audio_output])
|
357 |
-
|
358 |
-
gr.Examples(examples=image_upload_examples, inputs=[image_input, language_selector])
|
359 |
-
with gr.Tab("Description Search"):
|
360 |
-
gr.Markdown("<h2 id='description-search-text'>Description Search</h2>")
|
361 |
-
|
362 |
-
description_input = gr.Textbox(label="Enter a description (in English or Arabic)")
|
363 |
-
search_button = gr.Button("Search")
|
364 |
-
|
365 |
-
search_image_output = gr.Image(label="Matched Art Piece", elem_id="search_image_output")
|
366 |
-
search_description_output = gr.HTML(label="Art Piece Information")
|
367 |
-
search_audio_output = gr.Audio(label="Narration of the Story")
|
368 |
-
|
369 |
-
search_button.click(compare_description, inputs=description_input, outputs=[search_image_output, search_description_output, search_audio_output])
|
370 |
-
|
371 |
-
gr.Examples(examples=description_search_examples, inputs=description_input)
|
372 |
-
|
373 |
-
demo.launch()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|