I want to display an image produced by matplotlib in django.
I have a working solution but want to do it without writing to the disk.
Here is the code:
def __get_img_data1(): # not working - returns a white blank image
fig = plt.figure()
imgdata = StringIO.StringIO()
fig.savefig(imgdata, format='png')
imgdata.seek(0)
content = imgdata.getvalue()
imgdata.close()
return content
def __get_img_data2(): # not working - returns a broken image
fig = plt.figure()
imgdata = StringIO.StringIO()
fig.savefig(imgdata, format='png')
imgdata.seek(0)
from PIL import Image
return Image.open(imgdata)
def __get_img_data3(): # working!
img_file = NamedTemporaryFile(delete=False)
plt.savefig(img_file.name, dpi=600)
img_data = open(img_file.name + '.png', 'rb').read()
os.remove(img_file.name)
os.remove(img_file.name + '.png')
return img_data
I have taken 3 approaches shown above.
How to make it work without writing to the disk?
It is supposed to work according to the documentation:
http://matplotlib.org/faq/howto_faq.html
but it displays an empty white image.
uh, I figured out.
The problem is that I needed to get the figure object before doing my plotting.
This works:
def __get_png_img_buff(fig):
buff = StringIO.StringIO()
fig.savefig(buff, format='png')
buff.seek(0)
return buff
Related
I have created a object model as below
from django.db import models
# Create your models here.
class ImageModel(models.Model):
image = models.ImageField(upload_to='images/')
editedImg = models.ImageField(upload_to='images/')
def delete(self, *args, **kwargs):
self.image.delete()
self.editedImg.delete()
super().delete(*args, **kwargs)
And here is what i am trying to do in a function
from django.shortcuts import render
from EditorApp.forms import ImageForm
from EditorApp.models import ImageModel
from django.http import HttpResponseRedirect
from PIL import Image
def edit_column(request):
codArr = request.POST.getlist('codArr[]')
imgs = ImageModel.objects.first()
orgImage = ImageModel.objects.first().image
orgImage = Image.open(orgImage)
croppedImg = orgImage.crop((int(codArr[0]), int(codArr[1]), int(codArr[2]), int(codArr[3])))
# croppedImg.show()
# imgs.editedImg = croppedImg
# imgs.save()
return HttpResponseRedirect("/editing/")
What i am trying to do is the codArr consists of coordinates of top(x, y) and bottom(x, y) in the array form(Which is not an issue and is tested(croppedImg.show() showed the desired cropped image) and handled and used to crop the image). Image crop is working fine. But what i am trying to do is to save the cropped image in editedImg of the model used above. The above commented one is what i tried but throw a error AttributeError: _committed
As i have not used any name for image in model as its not required.
Kindly help please, Would be very thankfull.
you should do it like this:
from io import BytesIO
from api.models import ProductPicture
from django.core import files
codArr = request.POST.getlist('codArr[]')
img_obj = ImageModel.objects.first()
orgImage = img_obj.image
orgImage = Image.open(orgImage)
croppedImg = orgImage.crop((int(codArr[0]), int(codArr[1]), int(codArr[2]), int(codArr[3])))
thumb_io = BytesIO() # create a BytesIO object
croppedImg.save(thumb_io, 'png')
editedImg = files.File(thumb_io, name=file_name)
img_obj.editedImg = editedImg
img_obj.save()
You can use Python's context manager to open the image and save it to the desired storage in that case I'm using the images dir.
Pillow will crop the image and image.save() will save it to the filesystem and after that, you can add it to Django's ImageField and save it into the DB.
The context manager takes care of the file opening and closing, Pillow
takes care of the image, and Django takes care of the DB.
from PIL import Image
with Image.open(orgImage) as image:
file_name = image.filename # Can be replaced by orgImage filename
cropped_path = f"images/croped-{file_name}"
# The crop method from the Image module takes four coordinates as input.
# The right can also be represented as (left+width)
# and lower can be represented as (upper+height).
(left, upper, right, lower) = (20, 20, 100, 100)
# Here the image "image" is cropped and assigned to new variable im_crop
im_crop = image.crop((left, upper, right, lower))
im_crop.save(cropped_path)
imgs.editedImg = cropped_path
imgs.save()
Pillow's reference
I am running a streamlit app which generates reports containing images and dataframes. I have used jinja2 to generate the html file from a template. Then, I would now like to convert to a pdf file using xhtml2pdf to download.
How to do that?
from jinja2 import Environment, FileSystemLoader
def convert_html_to_pdf(source_html, output_filename="temp/report.pdf"):
result_file = io.BytesIO()
pdf = pisa.CreatePDF(
source_html,
dest=result_file)
return pdf.getvalue()
def load_template():
env = Environment(loader=FileSystemLoader('templates'))
template = env.get_template('catAnalysisTemplate.html')
return template
def render_report(data, filename="report"):
template = load_template()
html = template.render(data)
# with open(f'temp/{filename}.html', 'w') as f:
# f.write(html)
pdf = convert_html_to_pdf(html)
return [html, pdf]
This works fine except the images are not included in the pdf file. My static images are stored in
img/
logo.png
and the charts I may generate it in memory as like
def plot_co_attainment(qp):
img = io.BytesIO()
data = qp.co_attainment()[["Level", "Perc_Attainment"]]
plt.figure(dpi=150)
plt.bar(data["Level"], data["Perc_Attainment"], width=0.5, color=colors)
for i, val in enumerate(data["Perc_Attainment"].values):
plt.text(i, val, str(val) + "%",
horizontalalignment='center',
verticalalignment='bottom',
fontdict={'fontweight': 500, 'size': 20})
plt.xlabel("Course Outcomes")
plt.ylabel("Percentage of Attainment")
plt.ylim((0, 110))
plt.savefig(buf, format='jpg')
return buf
How do I connect the dots and get the images in my pdf file?
I am having the same issue. The way I solved it was to use a link_handler and return the data as a data: uri containing the png image data.
This example will take the src attribute and use it to generate a square image in that color, which will be embedded in the PDF. Sadly this doesn't let you modify the image tag itself so you can't change the sizes/classes or anything else.
Using something like this opens the way to embedding just about anything without having to add them to your template directly.
from base64 import b64encode
from io import BytesIO
from xhtml2pdf import pisa
from PIL import Image
html_src = """
<body>
<div>
<img src="red"/>
<img src="green"/>
<img src="blue"/>
</div>
</body>
"""
def link_callback(src_attr, *args):
"""
Returns the image data for use by the pdf renderer
"""
img_out = BytesIO()
img = Image.new("RGB", (100, 100), src_attr)
img.save(img_out, "png")
return f"data:image/png;base64,{b64encode(img_out.getvalue())}"
def main():
with open("one.pdf", "wb") as f:
pizza = pisa.CreatePDF(
html_src,
dest=f,
link_callback=link_callback,
)
if __name__ == "__main__":
main()
I am trying to obtain an image from a url and return it to the ModelAdmin to display it in a new column of the table.
I tried the following code in admin.py file:
def new_field(self, obj):
r = requests.get('https://abcd.com/image')
return r.content
The code is not giving me any error but it's returning a long binary string instead of the image itself.
How can I pass the image itself, or convert the binary content to an image?
You do not need download image if you wont only show it.
def new_field(self, obj):
url = 'https://abcd.com/image'
return '<img src="{}" />'.format(url)
new_field.allow_tags = True # it is important!!!
You can make use of a NamedTemporaryFile [GitHub] here. For example:
from django.core.files import File
from django.core.files.temp import NamedTemporaryFile
def store_image_from_source(self, obj):
img = NamedTemporaryFile()
r = requests.get('https://abcd.com/image')
img.write(r.content)
img.flush()
file = File(img)
obj.my_img_attr.save('filename.jpeg', file, save=True)
Here 'filename.jpeg' is thus te name of the file, as if you would have uploaded a file with that name with a ModelForm.
Im making a simple app that able to compress images with jpeg and png format using Pillow library, python3 and Django. Made a simple view that able to identify formats, save compress images and give some statistics of compressing. With images in jpeg format it works really fine, i got compressicons close to 70-80% of original size, and it works really fast, but if i upload png i works much worse. Compression takes a long time, and it only 3-5% of original size. Trying to find some ways to upgrade compress script, and stuck on it.
Right now ive got this script in my compress django view:
from django.shortcuts import render, redirect, get_object_or_404, reverse
from django.contrib.auth import login, authenticate, logout
from django.contrib.auth.models import User
from django.http import HttpResponse, HttpResponseRedirect
from django.http import JsonResponse
from django.contrib import auth
from .forms import InputForm, SignUpForm, LoginForm, FTPForm
import os
import sys
from PIL import Image
from .models import image, imagenew, FTPinput
from django.views import View
import datetime
from django.utils import timezone
import piexif
class BasicUploadView(View):
def get(self, request):
return render(self.request, 'main/index.html', {})
def post(self, request):
form = InputForm(self.request.POST, self.request.FILES)
if form.is_valid():
photo = form.save(commit=False)
photo.name = photo.image.name
photo.delete_time = timezone.now() + datetime.timedelta(hours=1)
photo.user = request.user
photo.size = photo.image.size
photo = form.save()
name = (photo.name).replace(' ', '_')
picture = Image.open(photo.image)
if picture.mode in ('RGB'):
piexif.remove('/home/andrey/sjimalka' + photo.image.url)
picture.save('media/new/'+name,"JPEG",optimize=True,quality=75)
newpic = 'new/'+name
new = imagenew.objects.create(
name = name,
image = newpic,
delete_time = timezone.now() + datetime.timedelta(hours=1),
user = request.user,
)
if new.image.size < photo.image.size:
diff = round((new.image.size-photo.image.size)/float(photo.image.size)*100, 2)
else:
diff = str(round((new.image.size-photo.image.size)/float(photo.image.size)*100, 2))+' Не удалось сжать файл'
oldsize = round(photo.image.size/1000000, 2)
newsize = round(new.image.size/1000000, 2)
id = new.pk
imagenew.objects.filter(pk=id).update(size=new.image.size)
elif picture.mode != ('RGB'):
picture.save('media/new/'+name,"PNG", optimize=True, quality=75)
newpic = 'new/'+name
new = imagenew.objects.create(
name = name,
image = newpic,
delete_time = timezone.now() + datetime.timedelta(hours=1),
user = request.user,
)
if new.image.size < photo.image.size:
diff = round((new.image.size-photo.image.size)/float(photo.image.size)*100, 2)
else:
diff = str(round((new.image.size-photo.image.size)/float(photo.image.size)*100, 2))+' Не удалось сжать файл'
oldsize = round(photo.image.size/1000000, 2)
newsize = round(new.image.size/1000000, 2)
id = new.pk
imagenew.objects.filter(pk=id).update(size=new.image.size)
data = {'is_valid': True, 'name': new.image.name, 'url': new.image.url, 'diff': diff,
'oldsize':oldsize, 'newsize':newsize,}
else:
alert = 'Данный формат не поддерживается. Пожалуйста загрузите картинки форматов png или jpg(jpeg)'
data = {'is_valid': False, 'name': alert,}
return JsonResponse(data)
The question: is there any ways to make script with png upload work faster, and (that much more important) make png size compressions closer to jpeg? Maybe i should use another python library?
how tinypng works then? They compressing same png files with 50-60%
They probably reduce the colour palette from 24-bit to 8-bit. Here's a detailed answer about that - https://stackoverflow.com/a/12146901/1925257
Basic method
You can try that in Pillow like this:
picture_8bit = picture.convert(
mode='P', # use mode='PA' for transparency
palette=Image.ADAPTIVE
)
picture_8bit.save(...) # do as usual
This should work similar to what tinypng does.
If you don't want transparency, it's better to first convert RGBA to RGB and then to P mode:
picture_rgb = picture.convert(mode='RGB') # convert RGBA to RGB
picture_8bit = picture_rgb.convert(mode='P', ...)
Getting better results
Calling convert() as shown above will actually call quantize() in the background and Median Cut algorithm will be used by default for reducing the colour palette.
In some cases, you'll get better results with other algorithms such as MAXCOVERAGE. To use a different algorithm, you can just call the quantize() method directly:
picture_rgb = picture.convert(mode='RGB') # convert RGBA to RGB
picture_8bit = picture.quantize(colors=256, method=Image.MAXCOVERAGE)
You have to understand that downsizing the colour palette means that if the image has lots of colours, you will be losing most of them because 8-bit can only contain 256 colours.
The document of Pillow Image.quatize displays a more convenient way to compress png files. In a personal experiment, the following code could make png about 70% compression of the original size, which is also close to the result created by ImageMagick.
# Image.quantize(colors=256, method=None, kmeans=0, palette=None)
# method: 0 = median cut; 1 = maximum coverage; 2 = fast octree
img = img.quantize(method=2)
Since google vision has some restrictions on input image size, I want to first resize input image and then use the detect_labels() function.
Here's their sample code
def detect_labels(path):
"""Detects labels in the file."""
vision_client = vision.Client()
with io.open(path, 'rb') as image_file:
content = image_file.read()
image = vision_client.image(content=content)
labels = image.detect_labels()
print('Labels:')
for label in labels:
print(label.description)
they use io to open the image file. I wonder in this way, how to resize the image in memory and then call detect_labels() ?
You can resize the image via PIL/Pillow and then pass it to the client:
replace
with io.open(path, 'rb') as image_file:
content = image_file.read()
with
# Warning: untested code, may require some fiddling
import Image, StringIO
img = Image.open(path)
img.thumbnail((512, 512))
buffer = StringIO.StringIO()
img.save(buffer, "PNG")
content = buffer.getvalue()
Code for python3:
Credits : #kristaps
import io
from PIL import Image
img = Image.open(path)
img.thumbnail((512, 512))
buffer = io.BytesIO()
img.save(buffer, "JPEG")
content = buffer.getvalue()