def get_pic(self):
time.sleep(2)
target = browser.find_element_by_class_name("yidun_bg-img")
template = browser.find_element_by_class_name("yidun_jigsaw")
target_link = target.get_attribute('src')
template_link = template.get_attribute('src')
target_img = Image.open(BytesIO(requests.get(target_link).content))
template_img = Image.open(BytesIO(requests.get(template_link).content))
target_img.save('target.jpg')
template_img.save('template.png')
size_orign = target.size
local_img = Image.open('target.jpg')
size_loc = local_img.size
self.zoom = 320 / int(size_loc[0])
def show(self) :
#open the image file from the path given
try : image = Image.open(self.image_path)
except IOError :
print "IOError"
return
image.show()
def show(self):
#open the image file from the path given
try:
image = Image.open(self.image_path)
except IOError:
print "IOError"
return
image.show()
def metadata_get_exif(self):
ret = {}
from PIL import Image
from PIL.ExifTags import TAGS
i = Image.open(self)
info = i._getexif()
for tag, value in info.items():
decoded = TAGS.get(tag, tag)
ret[decoded] = value
return ret
def get_png_grayvalue(filename):
try:
from pillow import Image
except:
import Image
I = Image.open(filename)
D = numpy.array(I.getdata())
if len(D.shape) > 1:
D = numpy.array(I.getdata())[:,0]
D = D.reshape((I.size[1],I.size[0]))
return D
def obscure(rects):
""" Takes an array of rects to obscure from the screenshot. """
image = Image.open('/tmp/.i3lock.png')
for rect in rects:
area = (rect.x, rect.y, rect.x + rect.width, rect.y + rect.height)
cropped = image.crop(area)
cropped = obscure_image(cropped)
image.paste(cropped, area)
image.save('/tmp/.i3lock.png')
def draw_image_rect(image_path, rects):
im = np.array(Image.open(image_path), dtype=np.uint8)
fig, ax = plt.subplots(1)
ax.imshow(im)
for rect in rects:
draw_rect = patches.Rectangle((rect[1], rect[0]),
rect[2],
rect[3],
linewidth=3,
edgecolor='b',
facecolor='none')
ax.add_patch(draw_rect)
plt.show()
def obscure(rects):
""" Takes an array of rects to obscure from the screenshot. """
image = Image.open('/tmp/.i3lock.png')
for rect in rects:
area = (
rect.x, rect.y,
rect.x + rect.width,
rect.y + rect.height
)
cropped = image.crop(area)
cropped = obscure_image(cropped)
image.paste(cropped, area)
image.save('/tmp/.i3lock.png')
def get_png_mask(filename):
try:
from pillow import Image
except:
try:
import Image
except:
import image as Image
I = Image.open(filename)
D = numpy.array(I.getdata())
if len(D.shape) > 1:
D = numpy.array(I.getdata())[:,0]
D = D.reshape((I.size[1],I.size[0]))
D = D[:,:]/255.
D = D.round()
D = numpy.int16(D)
return D
def __call__(self, jarvis, s):
if not s:
jarvis.say("please enter file path after calling the plugin")
elif not "png" in s:
jarvis.say("Your file must be a .png file")
else:
#We have to add the '.' back beacause the Jarvis API removes it
s = s.replace('png', '.' + 'png')
source_path = s
dest_path = s.replace('.png', '') + '.pdf'
image = Image.open(source_path)
pdf_bytes = img2pdf.convert(source_path.filename)
file = open(dest_path, "wb")
file.write(pdf_bytes)
image.close()
file.close()
jarvis.say("file successfully converted")
def runTest(self):
symbology = self.conf.symbology
img_prefix = join(IMG_ROOT, symbology)
for args in self.conf.cases:
img_filename, codestring = args[:2]
options = args[2] if len(args)>2 else {}
render_options = dict((args[3] if len(args)>3 else {}), scale=2.0)
generated = barcode(symbology, codestring, options, **render_options).convert('L')
loaded = Image.open(join(img_prefix, img_filename)).convert('L')
diff = None
try:
# image size comparison
self.assertEqual(generated.size, loaded.size)
# pixel-wize comparison
diff = ImageChops.difference(generated, loaded)
diff_bbox = diff.getbbox()
self.assertIsNone(diff_bbox)
except AssertionError as exc:
# generate and show diagnostics image
if diff:
# if diff exists, generate 3-row diagnostics image
lw, lh = loaded.size
gw, gh = generated.size
diag = Image.new('L', (max(lw, gw), (lh+gh+max(lh, gh))))
diag.paste(loaded, (0, 0, lw, lh))
diag.paste(generated, (0, lh, gw, lh+gh))
diag.paste(diff, (0, lh+gh, max(lw, gw), (lh+gh+max(lh, gh))))
else:
# else, just write generated image
diag = generated
sio_img = StringIO()
diag.convert('L').save(sio_img, 'PNG')
# reopen sio_img
sio_img = StringIO(sio_img.getvalue())
sio_uu = StringIO()
uuencode(sio_img, sio_uu, name='diag_%s' %img_filename)
raise AssertionError(
'Image difference detected (%s)\n'
'uu of generated image:\n----\n%s----\n'
%(exc.args, sio_uu.getvalue()))
#!C:\Anaconda3\Python
#coding=utf-8
from pillow import Image
print("=============== PIL ==================")
im = Image.open('00_10_ExternalClasses.png')
w, h = im.size
print('Original image size: %sx%s' % (w, h))
im.thumbnail((w//2, h//2))
print('Resize image to: %sx%s' % (w//2, h//2))
im.save('00_10_ExternalClasses_0.jpg', 'jpeg')
#! /usr/bin/env python3
from pillow import Image #图像处理模块
import numpy as np
a = np.asarray(Image.open("这里是原图片的路径").convert('L')).astype(
'float') #将图像以灰度图的方式打开并将数据转为float存入np中
depth = 10. # (0-100)
grad = np.gradient(a) #取图像灰度的梯度值
grad_x, grad_y = grad #分别取横纵图像梯度值
grad_x = grad_x * depth / 100.
grad_y = grad_y * depth / 100.
A = np.sqrt(grad_x**2 + grad_y**2 + 1.)
uni_x = grad_x / A
uni_y = grad_y / A
uni_z = 1. / A
#建立一个位于图像斜上方的虚拟光源
vec_el = np.pi / 2.2 # 光源的俯视角度，弧度值
vec_az = np.pi / 4. # 光源的方位角度，弧度值
dx = np.cos(vec_el) * np.cos(vec_az) #光源对x 轴的影响
dy = np.cos(vec_el) * np.sin(vec_az) #光源对y 轴的影响
dz = np.sin(vec_el) #光源对z 轴的影响
#计算各点新的像素值
b = 255 * (dx * uni_x + dy * uni_y + dz * uni_z) #光源归一化
b = b.clip(0, 255) #clip函数将区间外的数字剪除到区间边缘
im = Image.fromarray(b.astype('uint8')) #重构图像
im.save("这里是输出图片的路径")
def from_list(self, imlist, namelist, viz_bands, min, max, region,
folder, check=True, desclist=None, **kwargs):
""" Download every image and create the strip
:param imlist: Satellite Images (not PIL!!!!!!)
:type imlist: list of ee.Image
:param namelist: Names for the images. Must match imlist
:type namelist: list of str
:param desclist: list of descriptions for every image. Optional
:type desclist: list of str
:param viz_bands: Visualization bands. ej: ["NIR","SWIR","RED"]
:type viz_bands: list of str
:param min: min value for visualization
:type min: int
:param max: max value for visualization
:type max: int
:param region: coordinate list. Optional
:type region: list
:param folder: folder to downlaod files. Do not use '/' at the end
:type folder: str
:param check: Check if file exists, and if it does, omits the downlaod
:type check: bool
:param draw_polygons: Polygons to draw over the image. Must be a list of list of
coordinates. Optional
:type draw_polygons: list of list
:param draw_lines: Lines to draw over the image
:type draw_lines: list of list
:param draw_points: Points to draw over the image
:type draw_points: list of list
:param general_width: Images width
:type general_width: int
:return: A file with the name passed to StripImage() in the folder
passed to the method. Opens the generated file
"""
if isinstance(imlist, ee.List):
imlist = listEE2list(imlist, 'Image')
region = ee.Geometry.Polygon(region).bounds().getInfo()["coordinates"]
# TODO: modificar este metodo para que se pueda pasar listas de listas
general_width = kwargs.get("general_width", 500)
draw_polygons = kwargs.get("draw_polygons", None)
draw_lines = kwargs.get("draw_lines", None)
draw_points = kwargs.get("draw_points", None)
# desclist = kwargs.get("desclist", None)
list_of_lists = []
# logging.debug(("verificar archivo?", check))
# for i in range(0, len(imlist)):
for img_list, nom_list in zip(imlist, namelist):
pil_img_list = []
for image, name in zip(img_list, nom_list):
# name = namelist[i]
# exist = os.path.exists(folder+"/"+name)
# path = "{0}/{1}.{2}".format(folder, name, self.ext)
# CHECK CARPETA
abscarp = os.path.abspath(folder)
if not os.path.exists(abscarp):
os.mkdir(abscarp)
path = "{}/{}".format(folder, name)
fullpath = os.path.abspath(path)+"."+self.ext
exist = os.path.isfile(fullpath)
logging.debug(("existe {}?".format(fullpath), exist))
if check and exist:
im = ImPIL.open(fullpath)
else:
img = ee.Image(image)
urlviz = img.visualize(bands=viz_bands, min=min, max=max,
forceRgbOutput=True)
url = urlviz.getThumbURL({"region": region,
"format": self.ext,
"dimensions": general_width})
# archivo = funciones.downloadFile3(url, folder+"/"+name, self.ext)
file = batch.downloadFile(url, path, self.ext)
im = ImPIL.open(file.name)
# listaimPIL.append(im)
dr = ImageDraw.Draw(im)
general_width, general_height = im.size
# print "general_width:", general_width, "general_height:", general_height
# nivel de 'anidado' (nested)
def nested_level(l):
n = 0
while type(l[0]) is list:
n += 1
l = l[0]
return n
region = region[0] if nested_level(region) == 2 else region
region = region[:-1] if len(region) == 5 else region
p0 = region[0]
p1 = region[1]
p3 = region[3]
distX = abs(p0[0]-p1[0])
distY = abs(p0[1]-p3[1])
# FACTORES DE ESCALADO
width_ratio = float(general_width)/float(distX)
height_ratio = float(general_height)/float(distY)
if draw_polygons:
for pol in draw_polygons:
pol = [tuple(p) for p in pol]
newpol = [(abs(x-p0[0])*width_ratio, abs(y-p0[1])*height_ratio) for x, y in pol]
# logging.debug("nuevas coords {}".format(newpol))
#print "\n\n", pol, "\n\n"
dr.polygon(newpol, outline="red")
pil_img_list.append(im)
list_of_lists.append(pil_img_list)
if desclist:
return self.create(list_of_lists, namelist, desclist)
else:
return self.create(list_of_lists, namelist)
import pandas as pd
from pillow import Image
train_csv_path = "./msd-train/__DressType_msd_train-prod.csv"
train_csv = pd.read_csv(train_csv_path)
urls = train_csv["image_urls"] # list of all the image urls in the training CSV
alt_urls = train_csv[""
for img_path in image_paths:
with Image.open(img_path) as img:
width, height = img.size
from wand.image import Image
from pillow import Image as PI
import pyocr
import pyocr.builders
import io
tool = pyocr.get_available_tools()[0]
lang = tool.get_available_languages()[1]
req_image = []
final_text = []
image_pdf = Image(filename="C:/Users/jai/Desktop/Receipt - Generic.pdf", resolution=300)
image_jpeg = image_pdf.convert('jpeg')
for img in image_jpeg.sequence:
img_page = Image(image=img)
req_image.append(img_page.make_blob('jpeg'))
for img in req_image:
txt = tool.image_to_string(
PI.open(io.BytesIO(img)),
lang=lang,
builder=pyocr.builders.TextBuilder()
)
final_text.append(txt)
print (final_text)
def tiff_to_nparray(f):
im = Image.open(f)
imarray = np.array(im)
return imarray
import requests
from pillow import Image
from io import BytesIO
import csv
url = 'http://www.yswhosting.com/sandbox/don/images/padded/phi-delta-theta-tablecloth.jpg'
data = BytesIO(requests.get(url).content)
img = Image.open(data)
print 'a', img.size
output_file = "".join(
["../OutputData/GreekGear/", 'GreekGear.com-images-size.csv'])
print("output file is ", output_file)
final_csv_file = open(
output_file,
"wb") # binary mode to not add extra line breaks between rows in windows
writer = csv.writer(final_csv_file)
writer.writerow([img.size, url])
# import urllib, cStringIO
# from PIL import Image
# # given an object called 'link'
# #SITE_URL = "http://www.targetsite.com"
# #URL = SITE_URL + link['src']
# # Here's a sample url that works for demo purposes
# URL = "http://www.yswhosting.com/sandbox/don/images/padded/phi-delta-theta-tablecloth.jpg"
# file = cStringIO.StringIO(urllib.urlopen(URL).read())
# im=Image.open(file)
# print(im.size)
#width, height = im.size
Date()
now = datetime.now()
print("Проверено : ", datetime.strftime(datetime.now(), "%Y.%m.%d %H:%M:%S"))
while True:
var = int(
input("Введите вариант развития события(1 2 3 (0 для выхода))" + "\n"))
if var == 1:
for i, ii in enumerate(X1):
if X1[i] > max:
max = X1[i]
iter = i
img = Image.open('ptkRel1.jpg')
if max >= 0.00 and max <= 0.35:
mixer.music.load('looking.mp3')
if max >= 0.36 and max <= 0.60:
sost = V[1]
mixer.music.load('BPLA.mp3')
if max >= 0.61 and max <= 1.00:
sost = V[2]
mixer.music.load('Fireman.mp3')
print("Состояние: ", sost)
img.show()
mixer.music.play()
max = -1
__author__ = 'webon'
from pillow import Image
import glob, os
size = 200, 200
for infile in glob.glob('C:/Users/webon/Desktop/loan-officer-images.2902jpg'):
file, ext = os.path.splitext(infile)
im = Image.open(infile)
im.thumbnail(size)
im.save(file + '.thumbnail', 'JPEG')
# 图片格式转换, Jpg转Png
# 方法①
from pillow import Image
img = Image.open('test.jpg')
img.save('test1.png')
# 方法②
from cv2 import imread, imwrite
image = imread("test.jpg", 1)
imwrite("test2.png", image)
'''import cv2
import numpy as np
import pyzbar.pyzbar as pyzbar
image = cv2.imread("bca.jpg")
decodedObjects = pyzbar.decode(image)
for obj in decodedObjects:
print("obj", obj)
print("Type:", obj.type)
print("Data: ", obj.data, "\n")
cv2.imshow("Frame", image)
cv2.waitKey(0)
'''
from pillow import Image
from tesseract import image_to_string
print( image_to_string(Image.open('IMG_20200116_151537__01.jpg')) )
print( image_to_string(Image.open('IMG_20200116_151537__01.jpg'), lang='eng') )
