I'm trying to display a base64 encoded image aligned to some HTML text in Jupyter notebooks. The code below is an initial attempt - the image (downloaded from https://stackoverflow.com/company/logos) is show belown the text.
import base64
from io import BytesIO
from IPython.display import Image
from IPython.core.display import display, HTML
with open(r'H:\se-icon.png', 'rb') as f:
data = BytesIO(f.read())
dataEncoded = base64.b64encode(data.getvalue())
display(HTML('<h3>Some Text</h3>'))
display(Image(dataEncoded, format='png', width=100))
The desired output is something like below. Ideally I could use just HTML code, with the img tag, however this does not work for my particular case, as the output of the notebook is emailed on. Use of the img tag does not guarantee that the image is displayed.
Is there any way to display the image aligned to the HTML text?
Related
I have an image in the .svg format. How do I import it to python and add title and label the axes?
I tried the following:
img = plt.imread('./tune.svg')
But it throws an error. Is there a way to do this?
You'll need to read it as an XML file and manipulate its DOM tree. You could either use xml.dom or xml.etree.ElementTree. There are also third-party libraries such as lxml.
Following an example that uses a SVG file from Wikipedia (file version of July 26, 2016) showing the Cantons of Switzerland and changes the background colour of the canton of Zurich leverage xml.etree.ElementTree.
(The path representing the canton of Zurich has an attribute id with the value path2536.)
import xml.etree.ElementTree as ET
OUTPUT_FILE = r"C:\Temp\Switzerland.svg"
# read SVG file
with open("Kantone_der_Schweiz.svg", "r") as file:
# parse DOM
svg = ET.parse(file)
# find Path element of Canton of Zurich (ID: path2536)
canton_zurich = svg.find(".//*[#id='path2536']")
# replace style value
canton_zurich.set("style", "fill:#12e9a1")
# save updated SVG to file
with open(OUTPUT_FILE, "wb") as output_file:
svg.write(output_file, encoding="UTF-8")
Here some useful links:
https://developer.mozilla.org/en-US/docs/Web/SVG
https://www.datacamp.com/tutorial/python-xml-elementtree
https://developer.mozilla.org/en-US/docs/Web/XPath
https://devhints.io/xpath
Below another modified example that does not require downloading the SVG file manually and the modified SVG is plotted with matplotlib (since your question is tagged with matplotlib).
This example requires the following third-party libraries:
cairosvg, matplotlib, and PIL
import io
from urllib.request import Request, urlopen
import xml.etree.ElementTree as ET
import cairosvg
import matplotlib.pyplot as plt
from PIL import Image
SVG_URL = "https://upload.wikimedia.org/wikipedia/commons/8/8b/" \
"Kantone_der_Schweiz.svg"
request = Request(SVG_URL)
with urlopen(request) as response:
# read and parse SVG file from URL
svg = ET.parse(io.BytesIO(response.read()))
canton_zurich = svg.find(".//*[#id='path2536']")
canton_zurich.set("style", "fill:#12e9a1")
# get SVG as a string
svg_string = ET.tostring(svg.getroot())
# plot with matplotlib
# see also https://stackoverflow.com/a/70007704/42659
png = cairosvg.svg2png(svg_string)
image = Image.open(io.BytesIO(png))
plt.imshow(image)
I can do this OK both in js and php but not in python. I'm trying to pull a thumbnail image from google books api into a python variable.
The text objects are fine eg
newTitle = (parsed_json['items'][0]['volumeInfo']['title'])
isbn10 = (parsed_json['items'][0]['volumeInfo']['industryIdentifiers'][1]['identifier'])
isbn13 = (parsed_json['items'][0]['volumeInfo']['industryIdentifiers'][0]['identifier'])
The image is supplied in the api as follows. (if you put the http// url into a browser you see the image):
"imageLinks": {
"smallThumbnail": "http://books.google.com/books/content?id=XUnNDwAAQBAJ&printsec=frontcover&img=1&zoom=5&edge=curl&source=gbs_api",
"thumbnail": "http://books.google.com/books/content?id=XUnNDwAAQBAJ&printsec=frontcover&img=1&zoom=1&edge=curl&source=gbs_api"
I have tried the simple:
myImage = (parsed_json['items'][0]['volumeInfo']['imageLinks'][thumbnail])
which doesn't work.
I have installed pillow to provide image management:
from PIL import Image
img = Image.open("parsed_json['items'][0]['volumeInfo']['imageLinks'][thumbnail]") or
img = Image.open(parsed_json['items'][0]['volumeInfo']['imageLinks'][thumbnail])
which doesn't work. I have tried more complex arrangements:
from PIL import Image
import requests
from io import BytesIO
response = requests.get(parsed_json['items'][0]['volumeInfo']['imageLinks'][thumbnail])
img = Image.open(BytesIO(response.content))
but nothing seems to work. I have tried many other variations on these attempts. I have also, unsuccessfully tried to load the text that points to the thumbnail to try another route. I am confident that the "['items'][0]['volumeInfo']['imageLinks'][thumbnail]" is correct though my only way of testing whether the variable is properly loaded is to save it or if the line of code isn't working.
I didn't have problems downloading and opening the image.
I have use the following code
import requests
from PIL import Image
image_url = "https://books.google.com/books/content?id=XUnNDwAAQBAJ&printsec=frontcover&img=1&zoom=5&edge=curl&source=gbs_api"
r = requests.get(image_url)
with open("demo_image",'wb') as f:
f.write(r.content)
img = Image.open("demo_image")
I have a fillable PDF and I have filled out some of the fields and saved it.
I am able to add an image to the PDF using pdfrw and ReportLab; however, when the PDF is saved, the data entered into the fillable fields has disappeared.
Can anyone point me in the right direction so that I can add an image to a PDF while still maintaining the filled fields?
Here is the reproducible code:
An example PDF is here
from PIL import Image
from reportlab.pdfgen.canvas import Canvas
from pdfrw import PdfReader
from pdfrw.buildxobj import pagexobj
from pdfrw.toreportlab import makerl
inpfn = 'input.pdf'
outfn = 'output.pdf'
pages = PdfReader(inpfn).pages
page=pagexobj(pages[0])
canvas = Canvas(outfn)
canvas.doForm(makerl(canvas, page))
im = Image.open("photo.jpg")
canvas.drawInlineImage(im, 20, 175, width=100, height=60)
canvas.save()
Here is the output PDF. As you can see the image is there, but the fields are all empty.
I can verify that the data from the fields is present when the PDF is initially read by inspecting the structure of the PDF with:
for p in page:
for a in p['/Annots']:
print(a['/V'])
This prints out a bunch of data (with weird characters) but I can indeed see data that was entered into the form (e.g., "trade_name")
The main problem is that, from what I could find, there is no easy/documented way to load an image from base64 encoded image. I use the following code to encode the image to base64 (so that I wouldn't need to include all the images with the source, nor should I create temp files and delete them at exit). The image format I use is .png which is supported in Gtk3+. (from GdkPixbuf.Pixbuf.get_formats() i have ['png'] in the results. I am really confused on how to use Gtk3+ for this purpose.
import base64
image_name = 'image.png'
image_loc = 'd:\\Home\\' + image_name
with open(image_loc, 'rb') as image_file:
encoded_string = base64.b64encode(image_file.read())
print(encoded_string)
I want to use the output for example:
base64_data="""
iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAABsklEQVRYhe2XIVMCQRSAv2AwGAgEAuFmJBiMFmcMBH8AgUAgXHDMFww2gtFA
IBicsRgNBgLBcS7yE4gEIsFgIBDO8Pa8x7FwB7cnxTfzyr637327b+/dLiTSBIbAHIgydAGMgAscyUOOpDZdAu2iyZsq4BcwAHpb9NE1xFAl
P8s558klRFzzwQ5zejgsRxygVxBgbwiXAHtBuAaIIa7KBAgyACJgBlTKAqgBH8A0pWmIXKXYB2CbdFRM/xAA3qEBKipm8A9wCIAa8q/oUOJn
6FTKAqgA10gZWkD9rwAugRfWm1IEfCKlKQ2ghdwrstp0vwyAuiX5HGnRMwtE1zVAfLPS6hubZ7HNgaorgFPkppxOEvcBG0AE3LoCuGZ1Zb7R
hrGfqLGJ8h24ArhTcaYZvqHyDV0BtFWcGbLlHrJygCM1Nla+r5Cc0OcCAA3sNfaN3dtgDwDeSO5xzQIQthvRNoAlcA7yGFmowTFSmzz6jmwv
rL6wYp0Yv7HFttKMusC3xSmP3qs4/ZxzJiTn41c85N032mEHQqQBHacWs+mFvTSQa8ldSxW4Qb7zEDntAabmWn4A0clKl9nNvDwAAAAASUVO
RK5CYII
"""
And render the image from base64.
As a side note, on tkinter this was easily done with:
tkinter.PhotoImage(data=base64_data)
And then display the image where you needed it.
Getting back to Gtk3+, I didn't find a method of loading the image from base64. Even with GdkPixbuf.Pixbuf.new_from_data, I get a broken image. I have also tried with Gio.MemoryInputStream.new_from_bytes, but it says that the format of the image isn't supported.
Your data is base64 encoded, in order for Gtk3+ to use it, you must first decode it:
import base64
raw_data = base64.b64decode(data)
Then you were right with GdkPixbuf.Pixbuf.new_from_data:
(I cannot test, but I think this may work)
import base64
raw_data = base64.b64decode(data)
image = GdkPixbuf.Pixbuf.new_from_data(raw_data)
image_show_2.set_from_pixbuf(image)
Else you can do as you showed:
import base64
raw_data = base64.b64decode(data)
byting = GLib.Bytes(raw_data)
inputing = Gio.MemoryInputStream.new_from_bytes(byting)
image = GdkPixbuf.Pixbuf.new_from_data(inputing)
image_show_2.set_from_pixbuf(image)
I am looking to create base64 inline encoded data of images for display in a table using canvases. Python generates and creates the web page dynamically. As it stands python uses the Image module to create thumbnails. After all of the thumbnails are created Python then generates base64 data of each thumbnail and puts the b64 data into hidden spans on the user's webpage. A user then clicks check marks by each thumbnail relative to their interest. They then create a pdf file containing their selected images by clicking a generate pdf button. The JavaScript using jsPDF generates the hidden span b64 data to create the image files in the pdf file and then ultimately the pdf file.
I am looking to hopefully shave down Python script execution time and minimize some disk I/O operations by generating the base64 thumbnail data in memory while the script executes.
Here is an example of what I would like to accomplish.
import os, sys
import Image
size = 128, 128
im = Image.open("/original/image/1.jpeg")
im.thumbnail(size)
thumb = base64.b64encode(im)
This doesn't work sadly, get a TypeErorr -
TypeError: must be string or buffer, not instance
Any thoughts on how to accomplish this?
You first need to save the image again in JPEG format; using the im.tostring() method would otherwise return raw image data that no browser would recognize:
from io import BytesIO
output = BytesIO()
im.save(output, format='JPEG')
im_data = output.getvalue()
This you can then encode to base64:
image_data = base64.b64encode(im_data)
if not isinstance(image_data, str):
# Python 3, decode from bytes to string
image_data = image_data.decode()
data_url = 'data:image/jpg;base64,' + image_data
Here is one I made with this method:
data:image/jpg;base64,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
Unfortunately the Markdown parser doesn't let me use this as an actual image, but you can see it in action in a snippet instead:
<img src="data:image/jpg;base64,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"/>
In Python 3, you may need to use BytesIO:
from io import BytesIO
...
outputBuffer = BytesIO()
bg.save(outputBuffer, format='JPEG')
bgBase64Data = outputBuffer.getvalue()
# http://stackoverflow.com/q/16748083/2603230
return 'data:image/jpeg;base64,' + base64.b64encode(bgBase64Data).decode()
thumb = base64.b64encode(im.tostring())
I think would work
I use PNG when I save to the buffer. With JPEG the numpy arrays are a bit different.
import base64
import io
import numpy as np
from PIL import Image
image_path = 'dog.jpg'
img2 = np.array(Image.open(image_path))
# Numpy -> b64
buffered = io.BytesIO()
Image.fromarray(img2).save(buffered, format="PNG")
b64image = base64.b64encode(buffered.getvalue())
# b64 -> Numpy
img = np.array(Image.open(io.BytesIO(base64.b64decode(b64image))))
print(img.shape)
np.testing.assert_almost_equal(img, img2)
Note that it will be slower.