How to co-located two images using Python?
I have two very distinct files:
One is a TIF image (Sentinel-1 image) exported from Google Earth Engine, covering the whole region of the Arctic. You can download it here: https://drive.google.com/uc?export=download&id=1YvNp5lFUE7MzheFGQcHOQdel-GJUQDUl
The other is a NetCDF file (download it here: https://drive.google.com/uc?export=download&id=1i4OGCQhKlZ056H1YHq4hTb0EbEkl-pYd), that covers also the region of the Arctic. In addition to this one I have another NC files with the coordinates (can be downloaded here: https://drive.google.com/uc?export=download&id=1WVzZ--NnHSPkJmBqlGwXAN7abXM5_uNh).
Question is: How to collocate them?
I've tried to upload the NetCDF file (after converting it into a TIF) into Earth engine, but since it doesn't have a fixed grid it doesn't work. So this one is not a solution.
I tried to convert NetCFD into a tif, using:
gdal_translate -of GTiff NETCDF:"C:\PHD\leeModisMPF\MODIS_Meltpond_Fraction_CPOM_5km_daily_2020182.nc":daily_fraction C:\PHD\dom2.tiff -a_srs EPSG:4326 -a_ullr -180 57,8 180 90
and then, I tried to merge/stack them using:
import rioxarray
from rioxarray import merge
from rasterio.plot import show
items = [r'C:\PHD\fri1.tiff',
r'C:\PHD\S1image_2022_02_18.tif']
elements = []
for val in items:
rds = rioxarray.open_rasterio(val)
if rds.rio.crs != "EPSG:32643":
rds = rds.rio.reproject("EPSG:32643")
elements.append(rds)
merged = merge.merge_arrays(elements)#, nodata=0.0)
image = merged.values
show(image)
Btw: in the last case, I never used the NetCDF coordinate file..which could be important to ensure that both tiff and orginal nc have both the same coordinates...
Related
I have a large fits file (over 30,000 x 30,000) pixels. IRAF cannot handle this size of image. How can one crop a file of this size while retaining correct header information, as IRAF does when using its standard cropping mode?
You can do this sort of cropping with astropy.io.fits, though it's not trivial yet. Since astropy.io.fits uses memory mapping by default, it should be able to handle arbitrarily large files (within some practical limits). If you want non-python solutions, look here for details about postage stamp creation.
from astropy.io import fits
from astropy import wcs
f = fits.open('file.fits')
w = wcs.WCS(f[0].header)
newf = fits.PrimaryHDU()
newf.data = f[0].data[100:-100,100:-100]
newf.header = f[0].header
newf.header.update(w[100:-100,100:-100].to_header())
See also this pull request, which implements a convenience Cutout2D function, though this is not yet available in a released version of astropy. Its usage can be seen in the documentation, modified to include WCS:
from astropy.nddata import Cutout2D
position = (49.7, 100.1)
shape = (40, 50)
cutout = Cutout2D(f[0].data, position, shape, wcs=w)
There are more examples here
I've been trying to combine an image produced from a deforestation database called Hansen and a shapefile created in ArcGIS to make a georeference image. The script I've written so far is below but unable to figure out how to combine the two (I've tried several scripts including http://uk.mathworks.com/help/map/examples/creating-maps-using-mapshow.html?searchHighlight=overlay%20maps). Any assistance would be helpful!
Thank you,
Michelle
% Read in thresholded Hansen data
Data_FrenchGuiana = imread('FrenchGuiana_GFC_extract_thresholded.tif');
LossYear_FrenchGuiana = Data_FrenchGuiana(:,:,2);
LossYear_FrenchGuiana = double(LossYear_FrenchGuiana);
figure('color','white');
image(LossYear_FrenchGuiana)
imwrite(A,'LossYear_FrenchGuiana.tif')
country = shaperead('FrenchGuiana.shp');
figure mapshow(country);
xlabel('easting in meters')
ylabel('northing in meters')
Using python 3.4 in linux and windows, I'm trying to create qr code images from a list of string objects. I don't want to just store the image as a file because the list of strings may change frequently. I want to then tile all the objects and display the resulting image on screen for the user to scan with a barcode scanner. For the user to know which code to scan I need to add some text to the qr code image.
I can create the list of image objects correctly and they are in a list and calling .show on these objects displays them properly but I don't know how to treat these objects as a file object to open them. The object that is given to the open function, (img_list[0] in my case), in my add_text_to_img needs to support read, seek and tell methods. When I try this as is I get an attribute error. I've tried BytesIO and StringIO but I get an error message that Image.open does not support buffer interface. Maybe I am not doing that part correctly.
I'm sure there are several ways to do this, but what is the best way to open in memory objects as a file object?
from io import BytesIO
import qrcode
from PIL import ImageFont, ImageDraw, Image
def make_qr_image_list(code_list):
"""
:param code_list: a list of string objects to encode into QR code image
:return: a list of image or some type of other data objects
"""
img_list = []
for item in code_list:
qr = qrcode.QRCode(
version=None,
error_correction=qrcode.ERROR_CORRECT_L,
box_size=4,
border=10
)
qr.add_data(item)
qr_image = qr.make_image(fit=True)
img_list.append(qr_image)
return img_list
def add_text_to_img(text_list, img_list):
"""
While I was working on this, I am only saving the first image. Once
it's working, I'll save the rest of the images to a list.
:param text_list: a list of strings to add to the corresponding image.
:param img_list: the list containing the images already created from
the text_list
:return:
"""
base = Image.open(img_list[0])
# img = Image.frombytes(mode='P', size=(164,164), data=img_list[0])
text_img = Image.new('RGBA', base.size, (255,255,255,0))
font = ImageFont.truetype('sans-serif.ttf', 10)
draw = ImageDraw.Draw(text_img)
draw.text((0,-20),text_list[0], (0,0,255,128), font=font)
# include some method to save the images after the text
# has been added here. Shouldn't actually save to a file.
# Should be saved to memory/img_list
output = Image.alpha_composite(base,text_img)
output.show()
if __name__ == '__main__':
test_list = ['AlGaN','n-AlGaN','p-AlGaN','MQW','LED AlN-AlGaN']
image_list = make_qr_image_list(test_list)
add_text_to_img(test_list, image_list)
im = image_list[0]
im.save('/my_save_path/test_image.png')
im.show()
Edit: I've been using python for about a year and I feel like this is a pretty common thing to do but I'm not even sure that I'm looking up/searching for the right terms. What topics would you search for to answer this? If anyone can post a link or two to what I need to read up on regarding this, that would be very appreciated.
You already have PIL image objects; qr.make_image() returns the (a wrapper around) the right type of object and you do not need to open them again.
As such, all you need to do is:
base = img_list[0]
and go from there.
You do need to match image modes when compositing; QR codes are black-and-white images (mode 1), so either convert that or use the same mode in your text_img image object. The Image.alpha_composite() operation does require that both images have an alpha channel. Converting the base is easy:
base = img_list[0].convert('RGBA')
I'm looking at implementing a Caffe CNN which accepts two input images and a label (later perhaps other data) and was wondering if anyone was aware of the correct syntax in the prototxt file for doing this? Is it simply an IMAGE_DATA layer with additional tops? Or should I use separate IMAGE_DATA layers for each?
Thanks,
James
Edit: I have been using the HDF5_DATA layer lately for this and it is definitely the way to go.
HDF5 is a key value store, where each key is a string, and each value is a multi-dimensional array. Thus, to use the HDF5_DATA layer, just add a new key for each top you want to use, and set the value for that key to store the image you want to use. Writing these HDF5 files from python is easy:
import h5py
import numpy as np
filelist = []
for i in range(100):
image1 = get_some_image(i)
image2 = get_another_image(i)
filename = '/tmp/my_hdf5%d.h5' % i
with hypy.File(filename, 'w') as f:
f['data1'] = np.transpose(image1, (2, 0, 1))
f['data2'] = np.transpose(image2, (2, 0, 1))
filelist.append(filename)
with open('/tmp/filelist.txt', 'w') as f:
for filename in filelist:
f.write(filename + '\n')
Then simply set the source of the HDF5_DATA param to be '/tmp/filelist.txt', and set the tops to be "data1" and "data2".
I'm leaving the original response below:
====================================================
There are two good ways of doing this. The easiest is probably to use two separate IMAGE_DATA layers, one with the first image and label, and a second with the second image. Caffe retrieves images from LMDB or LEVELDB, which are key value stores, and assuming you create your two databases with corresponding images having the same integer id key, Caffe will in fact load the images correctly, and you can proceed to construct your net with the data/labels of both layers.
The problem with this approach is that having two data layers is not really very satisfying, and it doesn't scale very well if you want to do more advanced things like having non-integer labels for things like bounding boxes, etc. If you're prepared to make a time investment in this, you can do a better job by modifying the tools/convert_imageset.cpp file to stack images or other data across channels. For example you could create a datum with 6 channels - the first 3 for your first image's RGB, and the second 3 for your second image's RGB. After reading this in using the IMAGE_DATA layer, you can split the stream into two images using a SLICE layer with a slice_point at index 3 along the slice_dim = 1 dimension. If further down the road, you decide that you want to load even more complex assortments of data, you'll understand the encoding scheme and can write your own decoding layer based off of src/caffe/layers/data_layer.cpp to gain full control of the pipeline.
You may also consider using HDF5_DATA layer with multiple "top"s
I have a folder of jpg files and I want to make them into a movie. I am using this script:
% Create video out of list of jpgs
clear
clc
% Folder with all the image files you want to create a movie from, choose this folder using:
ImagesFolder = uigetdir;
% Verify that all the images are in the correct time order, this could be useful if you were using any kind of time lapse photography. We can do that by using dir to map our images and create a structure with information on each file.
jpegFiles = dir(strcat(ImagesFolder,'\*.jpg'));
% Sort by date from the datenum information.
S = [jpegFiles(:).datenum];
[S,S] = sort(S);
jpegFilesS = jpegFiles(S);
% The sub-structures within jpegFilesS is now sorted in ascending time order.
% Notice that datenum is a serial date number, for example, if you would like to get the time difference in hours between two images you need to subtract their datenum values and multiply by 1440.
% Create a VideoWriter object, in order to write video data to an .avi file using a jpeg compression.
VideoFile = strcat(ImagesFolder,'\MyVideo');
writerObj = VideoWriter(VideoFile);
% Define the video frames per second speed (fps)
fps = 1;
writerObj.FrameRate = fps;
% Open file for writing video data
open(writerObj);
% Running over all the files, converting them to movie frames using im2frame and writing the video data to file using writeVideo
for t = 1:length(jpegFilesS)
Frame = imread(strcat(ImagesFolder,'\',jpegFilesS(t).name));
writeVideo(writerObj,im2frame(Frame));
end
% Close the file after writing the video data
close(writerObj);
(Courtesy of http://imageprocessingblog.com/how-to-create-a-video-from-image-files/)
But it gives me this error:
Warning: No video frames were written to this file. The file may be invalid.
> In VideoWriter.VideoWriter>VideoWriter.close at 289
In Movie_jpgCompilation at 37
I'm sure my jpg files are fine, and they are in the folder I specify. What is the problem?
(This is my first post ever, so I hope it helps).
If you're on Linux, don't the backslashes need to be forward slashes? When I ran it on my Mac, my jpegFiles was an empty Struct. When I changed them around it worked:
% Create video out of list of jpgs
clear
clc
% Folder with all the image files you want to create a movie from, choose this folder using:
ImagesFolder = uigetdir;
% Verify that all the images are in the correct time order, this could be useful if you were using any kind of time lapse photography. We can do that by using dir to map our images and create a structure with information on each file.
jpegFiles = dir(strcat(ImagesFolder,'/*.jpg'));
% Sort by date from the datenum information.
S = [jpegFiles(:).datenum];
[S,S] = sort(S);
jpegFilesS = jpegFiles(S);
% The sub-structures within jpegFilesS is now sorted in ascending time order.
% Notice that datenum is a serial date number, for example, if you would like to get the time difference in hours between two images you need to subtract their datenum values and multiply by 1440.
% Create a VideoWriter object, in order to write video data to an .avi file using a jpeg compression.
VideoFile = strcat(ImagesFolder,'/MyVideo.avi');
writerObj = VideoWriter(VideoFile);
% Define the video frames per second speed (fps)
fps = 1;
writerObj.FrameRate = fps;
% Open file for writing video data
open(writerObj);
% Running over all the files, converting them to movie frames using im2frame and writing the video data to file using writeVideo
for t = 1:length(jpegFilesS)
Frame = imread(strcat(ImagesFolder,'/',jpegFilesS(t).name));
writeVideo(writerObj,im2frame(Frame));
end
% Close the file after writing the video data
close(writerObj);
Edit: You can also use filesep so that the file separator is OS-specific. http://www.mathworks.com/help/matlab/ref/filesep.html
It would be simpler to use Windows Movie Maker [windows] or iMovie [mac]. For your purposes though you should use PowerPoint.