AttributeError: 'int' object has no attribute 'decimal' about handheld-multi-frame-super-resolution HOT 4 CLOSED

Hello, I may have fixed the issue with the last commit: it had something to do the metada format which was slightly different from what we used during testing. The online demo has been updated too.

Please let me know is similar issues are persisting

from handheld-multi-frame-super-resolution.

Running it again and it results in this error:

DR=dr-limule-docker-gpu
Non-zero exit code (1): Parameters:

Upscaling factor: 2

Super-resolution with 25 images.

Robustness: enabled
-------------------------
t: 0.12
s1: 2.00
s2: 12.00
Mt: 0.80
Robustness denoising: enabled

Alignment:
-------------------------
ICA Iterations: 3

Fusion:
-------------------------
Kernel shape: handheld
k_stretch: 4.00
k_shrink: 2.00
k_detail: SNR based
k_denoise: SNR based

Processing with handheld super-resolution
Traceback (most recent call last):
File "/workdir/bin//demo.py", line 185, in
handheld_output, debug_dict = process(args.impath, options, params)
File "/workdir/bin/handheld_super_resolution/super_resolution.py", line 370, in process
ISO = int(str(tags['Image ISOSpeedRatings']))
KeyError: 'Image ISOSpeedRatings'

When I print the list of tags it tells me that the EXIF tag for the ISOSpeedRatings is EXIF ISOSpeedRatings not Image ISOSpeedRatings

After fixing that with a workaround (simply replacing Image with EXIF in that tag) and running it again I get this error:

FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\USER\\Handheld-Multi-Frame-Super-Resolution\\data\\noise_model_std_ISO_125.npy'

My workaround for this is to simply change line 370 of super_resolution.py from

ISO = max(100, ISO)

to

ISO = max(200, ISO)

After this I run into a CUDA support error as I don't have access to a machine with an NVIDIA GPU at the moment

from handheld-multi-frame-super-resolution.

Thank you for the feedback, I have updated the code so that the ISO can be read more consistently. It should also now be rounded when reading the noise curve, so this type of error should not happen.

from handheld-multi-frame-super-resolution.

Online demo runs successfully, now with good results

from handheld-multi-frame-super-resolution.