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How to read SEQ files produced by FLIR thermal infrared cameras?

I have some thermal infrared videos in .SEQ format captures with a FLIR camera. I can view them using FLIR Tools software, but I would like to instead read them into python, with every frame of the video being a numpy array containing temperature brightness values in each pixel.
I saw that the flirpy library (https://flirpy.readthedocs.io/en/latest/getting_started/seq.html) is able to covert .SEQ files to a different format, but I haven’t found any code examples for this, or any tool that can open the .SEQ files directly in python. If possible, I would prefer to work with the thermal files directly in python rather than covert them to a different file format.

There ist a file sdk from FLIR:
https://github.com/gcathelain/thermalcognition/tree/master/FLIR%20Science%20File%20SDK
the FileSDK can also be downloaded from FLIR directly: https://flir.custhelp.com/app/answers/detail/a_id/3504/~/getting-started-with-flir-science-file-sdk-for-python
Then you can install it directly for different python versions or also buiild wheel-files for an easier usage.
This directly supports the read out of the .seq-files via the package fnv. For me this is working fine and much faster than splitting by marker, which is sometimes done.

how to convert jpeg to tiff file in python

Is there any way to convert .jpeg to .tiff file?
If yes, then how to do that?
There are many library in Python that can convert file from one format to another.
But, I have not found anything for this problem.
Thanks in advance!

see this
from PIL import Image
im = Image.open('yourImg.jpg')
im.save("pathToSave/hello.tiff", 'TIFF')

You can use PIL (Python Imaging Library) for this:
import Image
im = Image.open('test.jpg')
im.save('test.tiff') # or 'test.tif'
Also, this was the first result for your problem on Google, make sure you google extensively first.

According to OpenCV docs for functions used for image and video reading and writing imread does support JPEG files and imwrite can save TIFF files, though with some limitations:
Only 8-bit (or 16-bit unsigned (CV_16U) in case of PNG, JPEG 2000, and TIFF) single-channel or 3-channel (with ‘BGR’ channel order) images can be saved using this function.

How to parse pixel data of an online image python

For a project I am needing to parse pixel data from a large number of online images. I realised it could well be faster to load the images into programme memory with a get request, carry out the required operations, then move onto the next image - removing the necessity for reading and writing these into storage. However in doing this I have ran into several problems, is there a not (overly) complicated way to do this?
Edit: I didn't include code as as far as I can tell everything I've seen (scikit-image, pillow, imagemagick) is a complete dead end. Not looking for somebody to write code for me, just a pointer in the right direction.

Its easy to load image directly from url.
import PIL
from PIL import Image
import urllib2
url = "https://cdn.pixabay.com/photo/2013/07/12/12/58/tv-test-pattern-146649_1280.png"
img = PIL.Image.open(urllib2.urlopen(url))
Image is now loaded.
Getting pixels is also easy: Get pixel's RGB using PIL

Python - Best way to find similar images in a directory

Here is the effect I am trying to achieve - Imagine a user submits an image, then a python script to cycle through each JPEG/PNG for a similar image in the current working directory.
Close to how Google image search works (when you submit your image and it returns similar ones). Should I use PIL or OpenCV?
Preferably using Python3.4 by the way, but Python 2.7 is fine.
Wilson

I mean, why not use both? It's trivial to convert PIL images into OpenCV images and vice-versa, and both have niche functions that can make your life easier. Pair them up with sklearn and numpy, and you're cooking with gas.

I created the undouble library in Python which seems a match for your issue.
It uses Hash functions to detect (near-)identical images in for example a directory. It works using a multi-step process of pre-processing the images (grayscaling, normalizing, and scaling), computing the image hash, and the grouping of images based on a threshold value.

Python: Manipulating a 16-bit .tiff image in PIL &/or pygame: convert to 8-bit somehow?

Hello all,
I am working on a program which determines the average colony size of yeast from a photograph, and it is working fine with the .bmp images I tested it on. The program uses pygame, and might use PIL later.
However, the camera/software combo we use in my lab will only save 16-bit grayscale tiff's, and pygame does not seem to be able to recognize 16-bit tiff's, only 8-bit. I have been reading up for the last few hours on easy ways around this, but even the Python Imaging Library does not seem to be able to work with 16-bit .tiff's, I've tried and I get "IOError: cannot identify image file".
import Image
img = Image.open("01 WT mm.tif")
My ultimate goal is to have this program be user-friendly and easy to install, so I'm trying to avoid adding additional modules or requiring people to install ImageMagick or something.
Does anyone know a simple workaround to this problem using freeware or pure python? I don't know too much about images: bit-depth manipulation is out of my scope. But I am fairly sure that I don't need all 16 bits, and that probably only around 8 actually have real data anyway. In fact, I once used ImageMagick to try to convert them, and this resulted in an all-white image: I've since read that I should use the command "-auto-levels" because the data does not actually encompass the 16-bit range.
I greatly appreciate your help, and apologize for my lack of knowledge.
P.S.: Does anyone have any tips on how to make my Python program easy for non-programmers to install? Is there a way, for example, to somehow bundle it with Python and pygame so it's only one install? Can this be done for both Windows and Mac? Thank you.
EDIT: I tried to open it in GIMP, and got 3 errors:
1) Incorrect count for field "DateTime" (27, expecting 20); tag trimmed
2) Sorry, can not handle images with 12-bit samples
3) Unsupported layout, no RGBA loader
What does this mean and how do I fit it?

py2exe is the way to go for packaging up your application if you are on a windows system.
Regarding the 16bit tiff issue:
This example http://ubuntuforums.org/showthread.php?t=1483265 shows how to convert for display using PIL.
Now for the unasked portion question: When doing image analysis, you want to maintain the highest dynamic range possible for as long as possible in your image manipulations - you lose less information that way. As you may or may not be aware, PIL provides you with many filters/transforms that would allow you enhance the contrast of an image, even out light levels, or perform edge detection. A future direction you might want to consider is displaying the original image (scaled to 8 bit of course) along side a scaled image that has been processed for edge detection.
Check out http://code.google.com/p/pyimp/wiki/screenshots for some more examples and sample code.

I would look at pylibtiff, which has a pure python tiff reader.
For bundling, your best bet is probably py2exe and py2app.

This is actually a 2 part question:
1) 16 bit image data mangling for Python - I usually use GDAL + Numpy. This might be a bit too much for your requirements, you can use PIL + Numpy instead.
2) Release engineering Python apps can get messy. Depending on how complex your app is you can get away with py2deb, py2app and py2exe. Learning distutils will help too.