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I wrote the following code to resize images in a folder to 100*100 and save the images in the same folder using for loop.I am wondering why it isn't working.
The following is the code I have written:
import cv2
import glob
images=glob.glob("*.jpg")
for image in images:
img=cv2.imread(image,0)
re=cv2.resize(img,(100,100))
cv2.imshow("Hey",re)
cv2.waitKey(500)
cv2.destroyAllWindows()
cv2.imwrite("resized_"+image,re)
I executed this:
nsu#NSU:~/Desktop/cryptology$ python3 img2.py
I got no error:
nsu#NSU:~/Desktop/cryptology$ python3 img2.py
nsu#NSU:~/Desktop/cryptology$
But the folder where i have saved the images and code is as it is...
what should i do?
**A viewer posted an answer which resulted the same.
**The problem MAY not be with the code.
**Please consider this
If you like you can use very robust module of python called Pillow for image manipulation, so first do pip3 install pillow
then run this code
from PIL import Image
import glob
images=glob.glob("*.jpg")
for im in images:
# print(im)
img = Image.open(im)
img = img.resize((100, 100), Image.ANTIALIAS)
img.save(im+'_resized.jpg')
hope it helps ... you need to improve the code if you want to keep the aspect ratio of the image
I have some code below that is supposed to convert a SVG image to a PNG. It runs without errors but creates a PNG file that is blank instead of one with the same image as the original SVG. I did find that it is not an error with cairo but more one relating to rsvg, which I got here.
import cairo
import rsvg
img = cairo.ImageSurface(cairo.FORMAT_ARGB32, 640,480)
ctx = cairo.Context(img)
handle= rsvghandler.Handle('example.svg')
handle.render_cairo(ctx)
img.write_to_png("svg.png")
I am using Python 3.6 on Windows 10.
I can't for the life of me figure out why it isn't displaying the correct picture. Any help would be hugely appreciated.
If your goal is to convert from SVG to PNG, I would recommend using Wand, as in the following script:
from wand.api import library
import wand.color
import wand.image
with wand.image.Image() as image:
with wand.color.Color('transparent') as background_color:
library.MagickSetBackgroundColor(image.wand,
background_color.resource)
image.read(blob=NAMEOFTHEFILE.read(), format="svg")
png_image = image.make_blob("png32")
with open(NAMEOFTHENEWFILE, "wb") as out:
out.write(png_image)
I would like to use an IPython notebook as a way to interactively analyze some genome charts I am making with Biopython's GenomeDiagram module. While there is extensive documentation on how to use matplotlib to get graphs inline in IPython notebook, GenomeDiagram uses the ReportLab toolkit which I don't think is supported for inline graphing in IPython.
I was thinking, however, that a way around this would be to write out the plot/genome diagram to a file and then open the image inline which would have the same result with something like this:
gd_diagram.write("test.png", "PNG")
display(file="test.png")
However, I can't figure out how to do this - or know if it's possible. So does anyone know if images can be opened/displayed in IPython?
Courtesy of this post, you can do the following:
from IPython.display import Image
Image(filename='test.png')
(official docs)
If you are trying to display an Image in this way inside a loop, then you need to wrap the Image constructor in a display method.
from IPython.display import Image, display
listOfImageNames = ['/path/to/images/1.png',
'/path/to/images/2.png']
for imageName in listOfImageNames:
display(Image(filename=imageName))
Note, until now posted solutions only work for png and jpg!
If you want it even easier without importing further libraries or you want to display an animated or not animated GIF File in your Ipython Notebook. Transform the line where you want to display it to markdown and use this nice short hack!
This will import and display a .jpg image in Jupyter (tested with Python 2.7 in Anaconda environment)
from IPython.display import display
from PIL import Image
path="/path/to/image.jpg"
display(Image.open(path))
You may need to install PIL
in Anaconda this is done by typing
conda install pillow
If you want to efficiently display big number of images I recommend using IPyPlot package
import ipyplot
ipyplot.plot_images(images_array, max_images=20, img_width=150)
There are some other useful functions in that package where you can display images in interactive tabs (separate tab for each label/class) which is very helpful for all the ML classification tasks.
You could use in html code in markdown section:
example:
<img src="https://www.tensorflow.org/images/colab_logo_32px.png" />
A cleaner Python3 version that use standard numpy, matplotlib and PIL. Merging the answer for opening from URL.
import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
pil_im = Image.open('image.png') #Take jpg + png
## Uncomment to open from URL
#import requests
#r = requests.get('https://www.vegvesen.no/public/webkamera/kamera?id=131206')
#pil_im = Image.open(BytesIO(r.content))
im_array = np.asarray(pil_im)
plt.imshow(im_array)
plt.show()
Courtesy of this page, I found this worked when the suggestions above didn't:
import PIL.Image
from cStringIO import StringIO
import IPython.display
import numpy as np
def showarray(a, fmt='png'):
a = np.uint8(a)
f = StringIO()
PIL.Image.fromarray(a).save(f, fmt)
IPython.display.display(IPython.display.Image(data=f.getvalue()))
from IPython.display import Image
Image(filename =r'C:\user\path')
I've seen some solutions and some wont work because of the raw directory, when adding codes like the one above, just remember to add 'r' before the directory. this should avoid this kind of error: (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape
If you are looking to embed your image into ipython notebook from the local host, you can do the following:
First: find the current local path:
# show current directory
import os
cwd = os.getcwd()
cwd
The result for example would be:
'C:\\Users\\lenovo\\Tutorials'
Next, embed your image as follows:
from IPython.display import display
from PIL import Image
path="C:\\Users\\lenovo\\Tutorials\\Data_Science\\DS images\\your_image.jpeg"
display(Image.open(path))
Make sure that you choose the right image type among jpg, jpeg or png.
Another option for plotting inline from an array of images could be:
import IPython
def showimg(a):
IPython.display.display(PIL.Image.fromarray(a))
where a is an array
a.shape
(720, 1280, 3)
You can directly use this instead of importing PIL
from IPython.display import Image, display
display(Image(base_image_path))
Another opt is:
from matplotlib import pyplot as plt
from io import BytesIO
from PIL import Image
import Ipython
f = BytesIO()
plt.savefig(f, format='png')
Ipython.display.display(Ipython.display.Image(data=f.getvalue()))
f.close()
When using GenomeDiagram with Jupyter (iPython), the easiest way to display images is by converting the GenomeDiagram to a PNG image. This can be wrapped using an IPython.display.Image object to make it display in the notebook.
from Bio.Graphics import GenomeDiagram
from Bio.SeqFeature import SeqFeature, FeatureLocation
from IPython.display import display, Image
gd_diagram = GenomeDiagram.Diagram("Test diagram")
gd_track_for_features = gd_diagram.new_track(1, name="Annotated Features")
gd_feature_set = gd_track_for_features.new_set()
gd_feature_set.add_feature(SeqFeature(FeatureLocation(25, 75), strand=+1))
gd_diagram.draw(format="linear", orientation="landscape", pagesize='A4',
fragments=1, start=0, end=100)
Image(gd_diagram.write_to_string("PNG"))
[See Notebook]
This is the solution using opencv-python, but it opens new windows which is busy in waiting
import cv2 # pip install opencv-python
image = cv2.imread("foo.png")
cv2.imshow('test',image)
cv2.waitKey(duration) # in milliseconds; duration=0 means waiting forever
cv2.destroyAllWindows()
if you don't want to display image in another window, using matplotlib or whatever instead cv2.imshow()
import cv2
import matplotlib.pyplot as plt
image = cv2.imread("foo.png")
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.show()
I'm reading in an image with OpenCV, and trying to do something with it in numpy (rotate 90deg). Viewing the result with imshow from matplotlib, it all seems to be working just fine - image is rotated. I can't use drawing methods from OpenCV on the new image, however. In the following code (I'm running this in a sagemath cloud worksheet):
%python
import cv2
import matplotlib.pyplot as plt
import numpy as np
import os, sys
image = np.array( cv2.imread('imagename.png') )
plt.imshow(image,cmap='gray')
image = np.array(np.rot90(image,3) ) # put it right side up
plt.imshow(image,cmap='gray')
cv2.rectangle(image,(0,0),(100,100),(255,0,0),2)
plt.imshow(image,cmap='gray')
I get the following error on the cv2.rectangle() command:
TypeError: Layout of the output array img is incompatible with cv::Mat (step[ndims-1] != elemsize or step[1] != elemsize*nchannels)
The error goes away if I use np.array(np.rot90(image,4) ) instead (i.e. rotate it 360). So it appears that the change in dimensions is messing it up. Does OpenCV store the dimensions somewhere internally that I need to update or something?
EDIT: Adding image = image.copy() after rot90() solved the problem. See rayryeng's answer below.
This is apparently a bug in the Python OpenCV wrapper. If you look at this question here: np.rot90() corrupts an opencv image, apparently doing a rotation that doesn't result back in the original dimensions corrupts the image and the OP in that post experiences the same error you are having. FWIW, I also experienced the same bug.... no idea why.
A way around this is to make a copy of the image after you rotate, and then show the image. This I can't really explain, but it seems to work. Also, make sure you call plt.show() at the end of your code to show the image:
import cv2
import matplotlib.pyplot as plt
import numpy as np
import os, sys
image = np.array( cv2.imread('imagename.png') )
plt.imshow(image,cmap='gray')
image = np.array(np.rot90(image,3) ) # put it right side up
image = image.copy() # Change
plt.imshow(image,cmap='gray')
cv2.rectangle(image,(0,0),(100,100),(255,0,0),2)
plt.imshow(image,cmap='gray')
plt.show() # Show image
I faced the same problem with numpy 1.11.2 and opencv 3.3.0. Not sure why, but this did the job for me.
Before using cv2.rectangle, add the line below:
image1 = image1.transpose((1,0)).astype(np.uint8).copy()
Reference
Convert data type works for my problem.
The image is of type np.int64 before the convert.
image = image.astype(np.int32) # convert data type
I would like to use an IPython notebook as a way to interactively analyze some genome charts I am making with Biopython's GenomeDiagram module. While there is extensive documentation on how to use matplotlib to get graphs inline in IPython notebook, GenomeDiagram uses the ReportLab toolkit which I don't think is supported for inline graphing in IPython.
I was thinking, however, that a way around this would be to write out the plot/genome diagram to a file and then open the image inline which would have the same result with something like this:
gd_diagram.write("test.png", "PNG")
display(file="test.png")
However, I can't figure out how to do this - or know if it's possible. So does anyone know if images can be opened/displayed in IPython?
Courtesy of this post, you can do the following:
from IPython.display import Image
Image(filename='test.png')
(official docs)
If you are trying to display an Image in this way inside a loop, then you need to wrap the Image constructor in a display method.
from IPython.display import Image, display
listOfImageNames = ['/path/to/images/1.png',
'/path/to/images/2.png']
for imageName in listOfImageNames:
display(Image(filename=imageName))
Note, until now posted solutions only work for png and jpg!
If you want it even easier without importing further libraries or you want to display an animated or not animated GIF File in your Ipython Notebook. Transform the line where you want to display it to markdown and use this nice short hack!
This will import and display a .jpg image in Jupyter (tested with Python 2.7 in Anaconda environment)
from IPython.display import display
from PIL import Image
path="/path/to/image.jpg"
display(Image.open(path))
You may need to install PIL
in Anaconda this is done by typing
conda install pillow
If you want to efficiently display big number of images I recommend using IPyPlot package
import ipyplot
ipyplot.plot_images(images_array, max_images=20, img_width=150)
There are some other useful functions in that package where you can display images in interactive tabs (separate tab for each label/class) which is very helpful for all the ML classification tasks.
You could use in html code in markdown section:
example:
<img src="https://www.tensorflow.org/images/colab_logo_32px.png" />
A cleaner Python3 version that use standard numpy, matplotlib and PIL. Merging the answer for opening from URL.
import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
pil_im = Image.open('image.png') #Take jpg + png
## Uncomment to open from URL
#import requests
#r = requests.get('https://www.vegvesen.no/public/webkamera/kamera?id=131206')
#pil_im = Image.open(BytesIO(r.content))
im_array = np.asarray(pil_im)
plt.imshow(im_array)
plt.show()
Courtesy of this page, I found this worked when the suggestions above didn't:
import PIL.Image
from cStringIO import StringIO
import IPython.display
import numpy as np
def showarray(a, fmt='png'):
a = np.uint8(a)
f = StringIO()
PIL.Image.fromarray(a).save(f, fmt)
IPython.display.display(IPython.display.Image(data=f.getvalue()))
from IPython.display import Image
Image(filename =r'C:\user\path')
I've seen some solutions and some wont work because of the raw directory, when adding codes like the one above, just remember to add 'r' before the directory. this should avoid this kind of error: (unicode error) 'unicodeescape' codec can't decode bytes in position 2-3: truncated \UXXXXXXXX escape
If you are looking to embed your image into ipython notebook from the local host, you can do the following:
First: find the current local path:
# show current directory
import os
cwd = os.getcwd()
cwd
The result for example would be:
'C:\\Users\\lenovo\\Tutorials'
Next, embed your image as follows:
from IPython.display import display
from PIL import Image
path="C:\\Users\\lenovo\\Tutorials\\Data_Science\\DS images\\your_image.jpeg"
display(Image.open(path))
Make sure that you choose the right image type among jpg, jpeg or png.
Another option for plotting inline from an array of images could be:
import IPython
def showimg(a):
IPython.display.display(PIL.Image.fromarray(a))
where a is an array
a.shape
(720, 1280, 3)
You can directly use this instead of importing PIL
from IPython.display import Image, display
display(Image(base_image_path))
Another opt is:
from matplotlib import pyplot as plt
from io import BytesIO
from PIL import Image
import Ipython
f = BytesIO()
plt.savefig(f, format='png')
Ipython.display.display(Ipython.display.Image(data=f.getvalue()))
f.close()
When using GenomeDiagram with Jupyter (iPython), the easiest way to display images is by converting the GenomeDiagram to a PNG image. This can be wrapped using an IPython.display.Image object to make it display in the notebook.
from Bio.Graphics import GenomeDiagram
from Bio.SeqFeature import SeqFeature, FeatureLocation
from IPython.display import display, Image
gd_diagram = GenomeDiagram.Diagram("Test diagram")
gd_track_for_features = gd_diagram.new_track(1, name="Annotated Features")
gd_feature_set = gd_track_for_features.new_set()
gd_feature_set.add_feature(SeqFeature(FeatureLocation(25, 75), strand=+1))
gd_diagram.draw(format="linear", orientation="landscape", pagesize='A4',
fragments=1, start=0, end=100)
Image(gd_diagram.write_to_string("PNG"))
[See Notebook]
This is the solution using opencv-python, but it opens new windows which is busy in waiting
import cv2 # pip install opencv-python
image = cv2.imread("foo.png")
cv2.imshow('test',image)
cv2.waitKey(duration) # in milliseconds; duration=0 means waiting forever
cv2.destroyAllWindows()
if you don't want to display image in another window, using matplotlib or whatever instead cv2.imshow()
import cv2
import matplotlib.pyplot as plt
image = cv2.imread("foo.png")
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.show()