Showing all the images with matplotlib - python

I'm using numpy and matplotlib to read all the images in the folder for image processing techniques. Although, I have done the part of reading image dataset from folders and process it with numpy array. But the problem, I'm facing is of showing all the images with matplotlib.imshow function. Everytime I want to show all the images with imshow function, unfortunately it just give me first image nothing else.
My code is below:
import os
import numpy as np
import matplotlib.pyplot as mpplot
import matplotlib.image as mpimg
images = []
path = "../path/to/folder"
for root, _, files in os.walk(path):
current_directory_path = os.path.abspath(root)
for f in files:
name, ext = os.path.splitext(f)
if ext == ".jpg":
current_image_path = os.path.join(current_directory_path,f)
current_image = mpimg.imread(current_image_path)
images.append(current_image)
for img in images:
print len(img.shape)
i = 0
for i in range(len(img.shape)):
mpplot.imshow(img)
mpplot.show()
I will be thankful if somebody can help me in this.
P.S. I'm pretty new with python, numpy and also at stackoverflow. So, please don't mind if the question is unclear or not direct.
Thanks,

About showing only one plot in one moment: please get familiar with matplotlib subplots.
Also, what is your problem that you are not iterating over images. You are calling img x-times.
Try to iterate over images as below:
for img in images:
mpplot.imshow(img)
mpplot.show()

I think what you need to add is mpplot.figure() before each mpplot.show(), this will open a new window for each image.

Related

Working with .tiff images in python for deep learning

I am currently working on a project using imaging flow cytometry images in python. the images are .tiff an example file name is image27_Ch1.ome.tiff . I am having a little trouble with opening these images. I have tried to use matplotlib and PIL and the tifffile library but whatever I try does not seem to work. It always tells me FileNotFoundError: [Errno 2] No such file or directory: 'C:/Users/zacha/Desktop/cell_images/27_Ch1.ome.tiff' . Although I double and triple-checked that the directory to the image is correct, even when I copy and paste the path to the image from the image properties itself it still gives me this error. I tried converting a few images into .png images and the code works and will load the images, this is not ideal because I have a data set of a few hundred thousand images. I was wondering if anyone out there in the StackOverflow universe knows how to deal with a problem like this or has dealt with .tiff images in python in the past. Below is some of the code that I have tried to open these images.
import matplotlib.pyplot as plt
path = 'C:/Users/zacha/Desktop/cell_images/27_Ch1.ome.tiff'
I = plt.imread(path)
from PIL import Image
path = 'C:/Users/zacha/Desktop/cell_images/27_Ch1.ome.tiff'
image = Image.open(path)
Thank you very much to whoever reads or answers this question.
Try rasterio and matplotlib
import rasterio
import matplotlib.pyplot as plt
src_path = "Your_sat_img.tif"
img = rasterio.open(src_path)
plt.figure(figsize=(22, 22))
plt.imshow(img.read([1,2,3]).transpose(1, 2, 0))
You can try this code to open any tiff file:
import rasterio
from rasterio.plot import show
tiff_img = rasterio.open('filename.tif')
show(tiff_img)

Create numpy array from images in different folders

I am a beginner with Python, scikit-learn and numpy. I have a set of folders with images for which I want to do apply different Machine Learning algorithms. I am however struggling to get these images into numpy data that I can use.
These are my prerequisites:
Each folder name holds the key to what the images are. For example /birds/abc123.jpg and /birds/def456.jpg are both "birds"
Each image is 100x100px jpg
I am using Python 2.7
There are 2800 images in total
This is my code as far as I have gotten:
# Standard scientific Python imports
import matplotlib.pyplot as plt
# Import datasets, classifiers and performance metrics
from sklearn import svm, metrics
import numpy as np
import os # Working with files and folders
from PIL import Image # Image processing
rootdir = os.getcwd()
key_array = []
pixel_arr = np.empty((0,10000), int)
for subdir, dirs, files in os.walk('data'):
dir_name = subdir.split("/")[-1]
if "x" in dir_name:
key_array.append(dir_name)
for file in files:
if ".DS_Store" not in file:
file = os.path.join(subdir, file)
im = Image.open(file)
im_bw = im.convert('1') #Black and white
new_np = np.array(im_bw2).reshape(1,-1)
print new_np.shape
pixel_arr = np.append(pixel_arr, new_np, axis=0)
What works in this code is the browsing through the folders, getting the folder names and fetching the correct files/images. What I cannot get to work is to create a numpy array that is 2800,10000 (or maybe the correct would be 10000,2800), i.e. 2800 rows with 10000 values in each.
This solution (that I am not sure if it works) is super slow though and I am quite sure that there must be a solution that is faster and more elegant than this!
How can I create this 2800x10000 numpy array, preferrably with the index number from the key_array attached?
If you don't need all the images at the same time, you can use a generator.
def get_images():
for subdir, dirs, files in os.walk('data'):
dir_name = subdir.split("/")[-1]
if "x" in dir_name:
key_array.append(dir_name)
for file in files:
if ".DS_Store" not in file:
file = os.path.join(subdir, file)
im = Image.open(file)
im_bw = im.convert('1') #Black and white
yield np.array(im_bw2).reshape(1,-1)
This way you don't hold all the images in memory at the same time, which will probably help you out.
The use the images you would then do:
for image in get_images():
...

Scan a folder having multiple images to find the darker images

I have a folder having bunch of images, out of which few images are almost dark like this: Dark Images, and few images are good images like this: Good images
Basically i am able to identify the darker images by using the below code, for the darker images the np.mean(image) comes below 0.1, and for good images it comes above 0.1 range:
from skimage import io, img_as_float
import numpy as np
image = io.imread('C:/Data/Testing/Image_0_5.jpg')
image = img_as_float(image)
print(np.mean(image))
But what i want is to pass the specific folder having all the images so that my code can parse through all the images, and list down the images having dark images. Need help on this.
Thanks for the direction guys, appreciated.
Here's my code:
import matplotlib.image as mpimg
import os
def load_images(folder):
images = []
for filename in os.listdir(folder):
img = mpimg.imread(os.path.join(folder, filename))
img = img_as_float(img)
#print(np.mean(img))
if img is not None:
images.append(img)
if(np.mean(img) < 0.1):
print filename
load_images('C:/Data/Testing')
I have achieved what i was looking for :)

Trying to read numpy array into opencv - cv2.imdecode returns empty argument

Just getting back into coding after a few years out. Trying to write a piece of code that can go through a folder with .fits files, read out the image data, convert them to an array, read them into opencv, then perform edge detection on them. I can get it working fine with .png files as I don't have to play with arrays. I've done a lot of reading about, and that's enabled me to get to this point. Problem is, img is currently being returned empty, which causes everything else to freak. Any ideas please? Any help would be gratefully received!
#import packages
import cv2
from matplotlim import pyplot as plt
import os
from astropy.io import fits
from skimage import img_as_uint
import numpy as np
#create array with filenames
data = []
for root, dirs, files in os.walk(r'/Users/hannah/Desktop/firefountain-testset'):
for file in files:
if file.endswith('.fits'):
data.append(file)
#start my loop through the folder
for i in data:
fn = i
#read fits image data
hdulist = fits.open(fn)
img_data = hdulist[1].data
#put fits data into array with dtype set as original
imgraw=np.array(img_data, dtype = np.uint8)
#convert to uint16
img = img_as_uint(imgraw)
#crop to area of interest then add into array - possibly don't need second line
imgcrop = img[210:255,227:277]
imgcroparr = np.array(imgcrop)
#attempt to read into cv2 - this is where it loses the data
#all fine before this point I believe
imgfinal = cv2.imdecode(imgcroparr, 0,)
plt.imshow(imgfinal)
#imgfinal returns blank.
google drive with .fits files I'm using, plus .png to show what they should look like
Updated my code
for i in data:
fn = i
imgraw = fits.getdata(fn)
imgcrop = imgraw[210:255,227:277]
img = cv2.imdecode(imgcrop, 0,)
plt.imshow(img)
This opens the fits files no issue and imgcrop works as expected. cv2.imdecode(imgcrop, 0), however, throws up the following:
error: /Users/jhelmus/anaconda/conda-bld/work/opencv-2.4.8/modules/highgui/src/loadsave.cpp:307: error: (-215) buf.data && buf.isContinuous() in function imdecode_
Can't find anything on this error in this context online, getting more and more confused. It's probably something very silly and basic that I've forgotten to do, but I can't see it.

Programmatically generate video or animated GIF in Python?

I have a series of images that I want to create a video from. Ideally I could specify a frame duration for each frame but a fixed frame rate would be fine too. I'm doing this in wxPython, so I can render to a wxDC or I can save the images to files, like PNG. Is there a Python library that will allow me to create either a video (AVI, MPG, etc) or an animated GIF from these frames?
Edit: I've already tried PIL and it doesn't seem to work. Can someone correct me with this conclusion or suggest another toolkit? This link seems to backup my conclusion regarding PIL: http://www.somethinkodd.com/oddthinking/2005/12/06/python-imaging-library-pil-and-animated-gifs/
I'd recommend not using images2gif from visvis because it has problems with PIL/Pillow and is not actively maintained (I should know, because I am the author).
Instead, please use imageio, which was developed to solve this problem and more, and is intended to stay.
Quick and dirty solution:
import imageio
images = []
for filename in filenames:
images.append(imageio.imread(filename))
imageio.mimsave('/path/to/movie.gif', images)
For longer movies, use the streaming approach:
import imageio
with imageio.get_writer('/path/to/movie.gif', mode='I') as writer:
for filename in filenames:
image = imageio.imread(filename)
writer.append_data(image)
Here's how you do it using only PIL (install with: pip install Pillow):
import glob
import contextlib
from PIL import Image
# filepaths
fp_in = "/path/to/image_*.png"
fp_out = "/path/to/image.gif"
# use exit stack to automatically close opened images
with contextlib.ExitStack() as stack:
# lazily load images
imgs = (stack.enter_context(Image.open(f))
for f in sorted(glob.glob(fp_in)))
# extract first image from iterator
img = next(imgs)
# https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html#gif
img.save(fp=fp_out, format='GIF', append_images=imgs,
save_all=True, duration=200, loop=0)
See docs: https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html#gif
Well, now I'm using ImageMagick. I save my frames as PNG files and then invoke ImageMagick's convert.exe from Python to create an animated GIF. The nice thing about this approach is I can specify a frame duration for each frame individually. Unfortunately this depends on ImageMagick being installed on the machine. They have a Python wrapper but it looks pretty crappy and unsupported. Still open to other suggestions.
As of June 2009 the originally cited blog post has a method to create animated GIFs in the comments. Download the script images2gif.py (formerly images2gif.py, update courtesy of #geographika).
Then, to reverse the frames in a gif, for instance:
#!/usr/bin/env python
from PIL import Image, ImageSequence
import sys, os
filename = sys.argv[1]
im = Image.open(filename)
original_duration = im.info['duration']
frames = [frame.copy() for frame in ImageSequence.Iterator(im)]
frames.reverse()
from images2gif import writeGif
writeGif("reverse_" + os.path.basename(filename), frames, duration=original_duration/1000.0, dither=0)
I used images2gif.py which was easy to use. It did seem to double the file size though..
26 110kb PNG files, I expected 26*110kb = 2860kb, but my_gif.GIF was 5.7mb
Also because the GIF was 8bit, the nice png's became a little fuzzy in the GIF
Here is the code I used:
__author__ = 'Robert'
from images2gif import writeGif
from PIL import Image
import os
file_names = sorted((fn for fn in os.listdir('.') if fn.endswith('.png')))
#['animationframa.png', 'animationframb.png', 'animationframc.png', ...] "
images = [Image.open(fn) for fn in file_names]
print writeGif.__doc__
# writeGif(filename, images, duration=0.1, loops=0, dither=1)
# Write an animated gif from the specified images.
# images should be a list of numpy arrays of PIL images.
# Numpy images of type float should have pixels between 0 and 1.
# Numpy images of other types are expected to have values between 0 and 255.
#images.extend(reversed(images)) #infinit loop will go backwards and forwards.
filename = "my_gif.GIF"
writeGif(filename, images, duration=0.2)
#54 frames written
#
#Process finished with exit code 0
Here are 3 of the 26 frames:
shrinking the images reduced the size:
size = (150,150)
for im in images:
im.thumbnail(size, Image.ANTIALIAS)
To create a video, you could use opencv,
#load your frames
frames = ...
#create a video writer
writer = cvCreateVideoWriter(filename, -1, fps, frame_size, is_color=1)
#and write your frames in a loop if you want
cvWriteFrame(writer, frames[i])
I came across this post and none of the solutions worked, so here is my solution that does work
Problems with other solutions thus far:
1) No explicit solution as to how the duration is modified
2) No solution for the out of order directory iteration, which is essential for GIFs
3) No explanation of how to install imageio for python 3
install imageio like this: python3 -m pip install imageio
Note: you'll want to make sure your frames have some sort of index in the filename so they can be sorted, otherwise you'll have no way of knowing where the GIF starts or ends
import imageio
import os
path = '/Users/myusername/Desktop/Pics/' # on Mac: right click on a folder, hold down option, and click "copy as pathname"
image_folder = os.fsencode(path)
filenames = []
for file in os.listdir(image_folder):
filename = os.fsdecode(file)
if filename.endswith( ('.jpeg', '.png', '.gif') ):
filenames.append(filename)
filenames.sort() # this iteration technique has no built in order, so sort the frames
images = list(map(lambda filename: imageio.imread(filename), filenames))
imageio.mimsave(os.path.join('movie.gif'), images, duration = 0.04) # modify duration as needed
Like Warren said last year, this is an old question. Since people still seem to be viewing the page, I'd like to redirect them to a more modern solution. Like blakev said here, there is a Pillow example on github.
import ImageSequence
import Image
import gifmaker
sequence = []
im = Image.open(....)
# im is your original image
frames = [frame.copy() for frame in ImageSequence.Iterator(im)]
# write GIF animation
fp = open("out.gif", "wb")
gifmaker.makedelta(fp, frames)
fp.close()
Note: This example is outdated (gifmaker is not an importable module, only a script). Pillow has a GifImagePlugin (whose source is on GitHub), but the doc on ImageSequence seems to indicate limited support (reading only)
Old question, lots of good answers, but there might still be interest in another alternative...
The numpngw module that I recently put up on github (https://github.com/WarrenWeckesser/numpngw) can write animated PNG files from numpy arrays. (Update: numpngw is now on pypi: https://pypi.python.org/pypi/numpngw.)
For example, this script:
import numpy as np
import numpngw
img0 = np.zeros((64, 64, 3), dtype=np.uint8)
img0[:32, :32, :] = 255
img1 = np.zeros((64, 64, 3), dtype=np.uint8)
img1[32:, :32, 0] = 255
img2 = np.zeros((64, 64, 3), dtype=np.uint8)
img2[32:, 32:, 1] = 255
img3 = np.zeros((64, 64, 3), dtype=np.uint8)
img3[:32, 32:, 2] = 255
seq = [img0, img1, img2, img3]
for img in seq:
img[16:-16, 16:-16] = 127
img[0, :] = 127
img[-1, :] = 127
img[:, 0] = 127
img[:, -1] = 127
numpngw.write_apng('foo.png', seq, delay=250, use_palette=True)
creates:
You'll need a browser that supports animated PNG (either directly or with a plugin) to see the animation.
As one member mentioned above, imageio is a great way to do this. imageio also allows you to set the frame rate, and I actually wrote a function in Python that allows you to set a hold on the final frame. I use this function for scientific animations where looping is useful but immediate restart isn't. Here is the link and the function:
How to make a GIF using Python
import matplotlib.pyplot as plt
import os
import imageio
def gif_maker(gif_name,png_dir,gif_indx,num_gifs,dpi=90):
# make png path if it doesn't exist already
if not os.path.exists(png_dir):
os.makedirs(png_dir)
# save each .png for GIF
# lower dpi gives a smaller, grainier GIF; higher dpi gives larger, clearer GIF
plt.savefig(png_dir+'frame_'+str(gif_indx)+'_.png',dpi=dpi)
plt.close('all') # comment this out if you're just updating the x,y data
if gif_indx==num_gifs-1:
# sort the .png files based on index used above
images,image_file_names = [],[]
for file_name in os.listdir(png_dir):
if file_name.endswith('.png'):
image_file_names.append(file_name)
sorted_files = sorted(image_file_names, key=lambda y: int(y.split('_')[1]))
# define some GIF parameters
frame_length = 0.5 # seconds between frames
end_pause = 4 # seconds to stay on last frame
# loop through files, join them to image array, and write to GIF called 'wind_turbine_dist.gif'
for ii in range(0,len(sorted_files)):
file_path = os.path.join(png_dir, sorted_files[ii])
if ii==len(sorted_files)-1:
for jj in range(0,int(end_pause/frame_length)):
images.append(imageio.imread(file_path))
else:
images.append(imageio.imread(file_path))
# the duration is the time spent on each image (1/duration is frame rate)
imageio.mimsave(gif_name, images,'GIF',duration=frame_length)
It's not a python library, but mencoder can do that: Encoding from multiple input image files. You can execute mencoder from python like this:
import os
os.system("mencoder ...")
Installation
pip install imageio-ffmpeg
pip install imageio
Code
import imageio
images = []
for filename in filenames:
images.append(imageio.imread(filename))
imageio.mimsave('movie.mp4', images)
Quality is raised and size is reduced from 8Mb to 80Kb when saving as mp4 than gif
from PIL import Image
import glob #use it if you want to read all of the certain file type in the directory
imgs=[]
for i in range(596,691):
imgs.append("snap"+str(i)+'.png')
print("scanned the image identified with",i)
starting and ending value+1 of the index that identifies different file names
imgs = glob.glob("*.png") #do this if you want to read all files ending with .png
my files were: snap596.png, snap597.png ...... snap690.png
frames = []
for i in imgs:
new_frame = Image.open(i)
frames.append(new_frame)
Save into a GIF file that loops forever
frames[0].save('fire3_PIL.gif', format='GIF',
append_images=frames[1:],
save_all=True,
duration=300, loop=0)
I found flickering issue with imageio and this method fixed it.
Have you tried PyMedia? I am not 100% sure but it looks like this tutorial example targets your problem.
With windows7, python2.7, opencv 3.0, the following works for me:
import cv2
import os
vvw = cv2.VideoWriter('mymovie.avi',cv2.VideoWriter_fourcc('X','V','I','D'),24,(640,480))
frameslist = os.listdir('.\\frames')
howmanyframes = len(frameslist)
print('Frames count: '+str(howmanyframes)) #just for debugging
for i in range(0,howmanyframes):
print(i)
theframe = cv2.imread('.\\frames\\'+frameslist[i])
vvw.write(theframe)
The easiest thing that makes it work for me is calling a shell command in Python.
If your images are stored such as dummy_image_1.png, dummy_image_2.png ... dummy_image_N.png, then you can use the function:
import subprocess
def grid2gif(image_str, output_gif):
str1 = 'convert -delay 100 -loop 1 ' + image_str + ' ' + output_gif
subprocess.call(str1, shell=True)
Just execute:
grid2gif("dummy_image*.png", "my_output.gif")
This will construct your gif file my_output.gif.
The task can be completed by running the two line python script from the same folder as the sequence of picture files. For png formatted files the script is -
from scitools.std import movie
movie('*.png',fps=1,output_file='thisismygif.gif')
I was looking for a single line code and found the following to work for my application. Here is what I did:
First Step: Install ImageMagick from the link below
https://www.imagemagick.org/script/download.php
Second Step: Point the cmd line to the folder where the images (in my case .png format) are placed
Third Step: Type the following command
magick -quality 100 *.png outvideo.mpeg
Thanks FogleBird for the idea!
Addition to Smart Manoj answers: Make a .mp4 movie from all images in a folder
Installation:
pip install imageio-ffmpeg
pip install imageio
Code:
import os
import imageio
root = r'path_to_folder_with_images'
images = []
for subdir, dirs, files in os.walk(root):
for file in files:
images.append(imageio.imread(os.path.join(root,file)))
savepath = r'path_to_save_folder'
imageio.mimsave(os.path.join(savepath,'movie.mp4'), images)
PS: Make sure your "files" list is sorted the way you want, you will save some time if you already save your images accordingly
A simple function that makes GIFs:
import imageio
import pathlib
from datetime import datetime
def make_gif(image_directory: pathlib.Path, frames_per_second: float, **kwargs):
"""
Makes a .gif which shows many images at a given frame rate.
All images should be in order (don't know how this works) in the image directory
Only tested with .png images but may work with others.
:param image_directory:
:type image_directory: pathlib.Path
:param frames_per_second:
:type frames_per_second: float
:param kwargs: image_type='png' or other
:return: nothing
"""
assert isinstance(image_directory, pathlib.Path), "input must be a pathlib object"
image_type = kwargs.get('type', 'png')
timestampStr = datetime.now().strftime("%y%m%d_%H%M%S")
gif_dir = image_directory.joinpath(timestampStr + "_GIF.gif")
print('Started making GIF')
print('Please wait... ')
images = []
for file_name in image_directory.glob('*.' + image_type):
images.append(imageio.imread(image_directory.joinpath(file_name)))
imageio.mimsave(gif_dir.as_posix(), images, fps=frames_per_second)
print('Finished making GIF!')
print('GIF can be found at: ' + gif_dir.as_posix())
def main():
fps = 2
png_dir = pathlib.Path('C:/temp/my_images')
make_gif(png_dir, fps)
if __name__ == "__main__":
main()
I just tried the following and was very useful:
First Download the libraries Figtodat and images2gif to your local directory.
Secondly Collect the figures in an array and convert them to an animated gif:
import sys
sys.path.insert(0,"/path/to/your/local/directory")
import Figtodat
from images2gif import writeGif
import matplotlib.pyplot as plt
import numpy
figure = plt.figure()
plot = figure.add_subplot (111)
plot.hold(False)
# draw a cardinal sine plot
images=[]
y = numpy.random.randn(100,5)
for i in range(y.shape[1]):
plot.plot (numpy.sin(y[:,i]))
plot.set_ylim(-3.0,3)
plot.text(90,-2.5,str(i))
im = Figtodat.fig2img(figure)
images.append(im)
writeGif("images.gif",images,duration=0.3,dither=0)
I came upon PIL's ImageSequence module, which offers for a better (and more standard) GIF aninmation. I also use Tk's after() method this time, which is better than time.sleep().
from Tkinter import *
from PIL import Image, ImageTk, ImageSequence
def stop(event):
global play
play = False
exit()
root = Tk()
root.bind("<Key>", stop) # Press any key to stop
GIFfile = {path_to_your_GIF_file}
im = Image.open(GIFfile); img = ImageTk.PhotoImage(im)
delay = im.info['duration'] # Delay used in the GIF file
lbl = Label(image=img); lbl.pack() # Create a label where to display images
play = True;
while play:
for frame in ImageSequence.Iterator(im):
if not play: break
root.after(delay);
img = ImageTk.PhotoImage(frame)
lbl.config(image=img); root.update() # Show the new frame/image
root.mainloop()
It's really incredible ... All are proposing some special package for playing an animated GIF, at the moment that it can be done with Tkinter and the classic PIL module!
Here is my own GIF animation method (I created a while ago). Very simple:
from Tkinter import *
from PIL import Image, ImageTk
from time import sleep
def stop(event):
global play
play = False
exit()
root = Tk()
root.bind("<Key>", stop) # Press any key to stop
GIFfile = {path_to_your_GIF_file}
im = Image.open(GIFfile); img = ImageTk.PhotoImage(im)
delay = float(im.info['duration'])/1000; # Delay used in the GIF file
lbl = Label(image=img); lbl.pack() # Create a label where to display images
play = True; frame = 0
while play:
sleep(delay);
frame += 1
try:
im.seek(frame); img = ImageTk.PhotoImage(im)
lbl.config(image=img); root.update() # Show the new frame/image
except EOFError:
frame = 0 # Restart
root.mainloop()
You can set your own means to stop the animation. Let me know if you like to get the full version with play/pause/quit buttons.
Note: I am not sure if the consecutive frames are read from memory or from the file (disk). In the second case it would be more efficient if they all read at once and saved into an array (list). (I'm not so interested to find out! :)
I understand you asked about converting images to a gif; however, if the original format is MP4, you could use FFmpeg:
ffmpeg -i input.mp4 output.gif

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