xyq1113723547/hdr-imaging

An implementation of "Paul E. Debevec, Jitendra Malik, Recovering High Dynamic Range Radiance Maps from Photographs, SIGGRAPH 1997."

HDR imaging

Requirement

• python3 (or higher)
• opencv 3.0 (or higher)

You will need to install some package using pip3:

• numpy
• matplotlib

Usage

$ python HDR-playground.py <input img dir> <output .hdr name>

# for example
$ python ./HDR-playground.py taipei taipei.hdr

I also provide an jupyter version(HDR-playground.ipynb), it’s function is same as HDR-playground.py. jupyter is really convenient for develop python program!

Input format

The input dir should have:

• Some .png images
• A image_list.txt, file should contain:
  • filename
  • exposure
  • 1/shutter_speed

This is an example for image_list.txt:

# Filename   exposure 1/shutter_speed
DSC_0058.png 32        0.03125
DSC_0059.png 16        0.0625
DSC_0060.png  8        0.125
DSC_0061.png  4        0.25
DSC_0062.png  2        0.5
DSC_0063.png  1        1
DSC_0064.png  0.5      2
DSC_0065.png  0.25     4
DSC_0066.png  0.125    8
DSC_0067.png  0.0625  16

Output

The program will output:

• A .hdr image
• A reconstruct RGB response curve plot
• A pseudo-color radiance map(with log value)

for sample output, you can see HDR-playground.ipynb as reference.

Tonemap

I use tmo for tonemapping, it implement 24 algorithms.
I write a script tonemap.bat for auto-run all 24 algorithms.

$ tonemap.bat <filename without extension>

Make sure all tm_*.exe is in your system PATH

Environment

I test my code in Window10, but it should work fine in macOS/Linux(exclude tonemapping reference program need run in Windows)