def as_gif(self, duration=100):
"""
Helpful to visualize it in a notebook
"""
self.labeled_frames[0]['frame'].save(
"/tmp/out.gif",
save_all=True,
append_images=[f['frame'] for f in self.labeled_frames[1:]],
duration=duration,
loop=0,
)
return IPythonImage(filename="/tmp/out.gif")
def show(self):
return IPythonImage(self._thumbnail)
bottom,
font=album_name_font,
fill=outline_color)
draw.text((band_x, band_y), top, (255, 255, 255), font=band_name_font)
draw.text((album_x, album_y),
bottom, (255, 255, 255),
font=album_name_font)
return img
img = display_cover(top='top', bottom='bottom')
img.save('sample-out.png')
## Use the following to read the img file and display the results
IPythonImage(filename='sample-out.png')
## Display an image with the text 'Python' on top and 'Data Science' below
img = display_cover(top='Python', bottom='Data Science')
img.save('sample-out.png')
IPythonImage(filename='sample-out.png')
## LOAD WIKIPEDIA PAGE
import requests
wikipedia_link = 'https://en.wikipedia.org/wiki/Special:Random'
raw_random_wikipedia_page = requests.get(wikipedia_link)
## Grab text file with the page's XML
page = raw_random_wikipedia_page.text
## print(page)
title_begin_index = page.find("<title>") + 7
a=page.find('<title>')
b=page.find('</title>')
c=len('<title>')
d=page[a+c:b]
band_title=d.replace(' - Wikipedia','')
wikipedia_link='https://en.wikipedia.org/wiki/Special:Random'
raw_random_wikipedia_page=requests.get(wikipedia_link)
page=raw_random_wikipedia_page.text
print(page)
a=page.find('<title>')
b=page.find('</title>')
c=len('<title>')
d=page[a+c:b]
album_title=d.replace(' - Wikipedia','')
print("Your band: ", band_title)
print("Your album: ", album_title)
img=display_cover(top=band_title,bottom=album_title)
img.save('gaurav2.png')
IPythonImage(filename='gaurav.png')
IPythonImage(filename='gaurav2.png')
def display_img(img_path):
img = IPythonImage(filename=img_path)
st.image(Image.open(img))
def display_cover(top, bottom):
import requests
img = display_cover(top='top', bottom='bottom')
name = 'album_art_raw.png'
# Now let's make get an album cover.
# https://picsum.photos/ is a free service that offers random images.
# Let's get a random image:
album_art_raw = requests.get('https://picsum.photos/500/500/?random')
img.save('album_art_raw.png')
IPythonImage(filename='album_art_raw.png')
# and save it as 'album_art_raw.png'
with open(name, 'wb') as album_art_raw_file:
album_art_raw_file.write(album_art_raw.content)
# Now that we have our raw image, let's open it
# and write our band and album name on it
img = Image.open("album_art_raw.png")
draw = ImageDraw.Draw(img)
# We'll choose a font for our band and album title,
# run "% ls /usr/share/fonts/truetype/dejavu" in a cell to see what else is available,
# or download your own .ttf fonts!
band_name_font = ImageFont.truetype(
"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
25) # 25pt font
album_name_font = ImageFont.truetype(
"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
20) # 20pt font
# the x,y coordinates for where our album name and band name text will start
# counted from the top left of the picture (in pixels)
band_x, band_y = 50, 50
album_x, album_y = 50, 400
# Our text should be visible on any image. A good way
# of accomplishing that is to use white text with a
# black border. We'll use the technique shown here to draw the border:
# https://mail.python.org/pipermail/image-sig/2009-May/005681.html
outline_color = "black"
draw.text((band_x - 1, band_y - 1),
top,
font=band_name_font,
fill=outline_color)
draw.text((band_x + 1, band_y - 1),
top,
font=band_name_font,
fill=outline_color)
draw.text((band_x - 1, band_y + 1),
top,
font=band_name_font,
fill=outline_color)
draw.text((band_x + 1, band_y + 1),
top,
font=band_name_font,
fill=outline_color)
draw.text((album_x - 1, album_y - 1),
bottom,
font=album_name_font,
fill=outline_color)
draw.text((album_x + 1, album_y - 1),
bottom,
font=album_name_font,
fill=outline_color)
draw.text((album_x - 1, album_y + 1),
bottom,
font=album_name_font,
fill=outline_color)
draw.text((album_x + 1, album_y + 1),
bottom,
font=album_name_font,
fill=outline_color)
draw.text((band_x, band_y), top, (255, 255, 255), font=band_name_font)
draw.text((album_x, album_y),
bottom, (255, 255, 255),
font=album_name_font)
return img
#创建模型
model = create_model(optimizer='Adam',
kernel_initializer='uniform',
activation='relu')
model.summary()
#----------------------------------------------------------------
# 第七步 模型绘制
#----------------------------------------------------------------
from keras.utils.vis_utils import plot_model
from IPython.display import Image as IPythonImage
plot_model(model, to_file="model.png", show_shapes=True)
display(IPythonImage('model.png'))
#----------------------------------------------------------------
# 第八步 模型训练+输出结果
#----------------------------------------------------------------
from keras.callbacks import ModelCheckpoint
from sklearn.metrics import classification_report
import matplotlib.pyplot as plt
#绘制图形
def plot_loss_accuracy(history):
# Loss
plt.figure(figsize=[8, 6])
plt.plot(history.history['loss'], 'r', linewidth=3.0)
plt.plot(history.history['val_loss'], 'b', linewidth=3.0)
def get_band_album_titles():
wikipedia_link = 'https://en.wikipedia.org/wiki/Special:Random'
raw_random_wikipedia_page = requests.get(wikipedia_link)
tree = fromstring(raw_random_wikipedia_page.content)
raw_title = tree.findtext('.//title')
band_title = raw_title.split('-')
raw_random_wikipedia_page = requests.get(wikipedia_link)
tree = fromstring(raw_random_wikipedia_page.content)
raw_title = tree.findtext('.//title')
album_title = raw_title.split('-')
return (band_title[0].rstrip() + '-' + album_title[0].rstrip())
# first part use data science and python as bottom and top
img = display_cover(top='Python', bottom='Data Science')
img.save('sample-out.png')
IPythonImage(filename='sample-out.png')
# second part capture two random titles and make them top and bottom text
band_title, album_title = get_band_album_titles().split('-')
album_cover = display_cover(top=band_title, bottom=album_title)
album_cover.save('album-cover.png')
IPythonImage(filename='album-cover.png')
"""
Распознавание продуктов
"""
# Для решения данной задачи в работе Viola Jones были использованы
# (cascade object detection with AdaBoost learning algorithm) и
# Histogram of Oriented Gradients (HOG).
# получилась следующая точность
from IPython.display import Image as IPythonImage
IPythonImage('docs/images/packs_detection_accuracy.png', width=600)
# сделав несколько улучшений получились рез-ты
IPythonImage('docs/images/packs_detection_accuracy_improved.png', width=600)
# Следующие задач компьюетрного зрения успешно решаются сейчас
IPythonImage('docs/images/cv_common_tasks.png', width=800)
# Модели https://github.com/tensorflow/models/tree/master/research/deeplab
# успешно решают задачи семантической сегментации
# Модели https://github.com/tensorflow/models/tree/master/research/object_detection
# решают задачи нахождения предметов
# Для распознавания пачек используем модель SSD Mobilenet V1
# натренированную на датасете COCO
import cv2
import pandas as pd
import numpy as np
import os
import io
import tensorflow as tf
import requests as rq
# In[31]:
album_raw = rq.get("https://raw.githubusercontent.com/arneec/digits-recognition/master/5.jpg") # random images
with open("image.jpg",'wb') as raw_file: #widthbairer
raw_file.write(album_raw.content)
# In[32]:
img = Image.open("image.jpg")
IPythonImage(filename= 'image.jpg') #To display the image
# In[33]:
img=misc.imread("image.jpg")
# In[34]:
print(features.shape)
# In[35]:
draw.text((album_x + 1, album_y + 1),
bottom,
font=album_name_font,
fill=outline_color)
draw.text((band_x, band_y), top, (255, 255, 255), font=band_name_font)
draw.text((album_x, album_y),
bottom, (255, 255, 255),
font=album_name_font)
return img
img = display_cover(top='top', bottom='bottom')
img.save('sample-out.png')
IPythonImage(filename='sample-out.png')
album_cover = display_cover(top="Python", bottom="Data Science")
album_cover.save("album-cover-out.png")
IPythonImage(filename="album-cover-out.png")
# -------------------------------------------------------------------------------------
wikipedia_link = 'https://en.wikipedia.org/wiki/Special:Random'
raw_random_wikipedia_page = requests.get(wikipedia_link)
page = raw_random_wikipedia_page.text
#print(page)
band_title = page[page.find('<title>') + 7:page.find(' - Wikipedia')]
#band_title