photo4d 0.2.0

Open source project to perform time-lapse photogrammetry

Photo4D: open-source time-lapse photogrammetry

Contributors by alphabetical orders:

• Simon Filhol ([e-mail])
• Luc Girod ([e-mail])
• Alexis Perret ([e-mail])
• Guillaume Sutter ([e-mail])

Description

This project consists of an automated program to generate point cloud from time-lapse set of images from independent cameras. The software:

1. sorts images by timestamps,
2. assess the image quality based on lumincace and bluriness,
3. identify automatically GCPs through the stacks of images,
4. run Micmac to compute point clouds, and
5. convert point cloud to rasters. (not implemented)

The project should be based on open-source libraries, for public release.

Installation

1. install the latest version of micmac

2. install python 3.6, and with anaconda, create a virtual environment with the following packages:

   • opencv
   • pandas
   • matplotlib
   • lxml
   • pillow
   • pyxif (that needs to be downloaded from https://github.com/zenwerk/Pyxif)

   wget https://github.com/zenwerk/Pyxif/archive/master.zip
   unzip Pyxif-master.zip
   cd Pyxif-master
   python setup.py install
   

3. The package is available via Pypi

   pip install photo4d
   

Usage

1. prepare your environment:
   • create a Python >= 3.6 virtual environment in which you install the required libraries (see above)
   • create a folder for the project with inside the project folder a folder called Images containing itself one folder per
   • Organize your photo with one folder per camera. For instance folder /cam1 constains all the images from Camera 1. camera

├── Project
    └── Images
         ├── Cam1
         ├── Cam2
         ├── Cam3
         └── Cam...

2. Set the path correctly in the file MicmacApp/Class_photo4D.py

############################################################
## Part 1

import photo4d as p4d

# Create a new photo4d object by indicating the Project path
myproj = p4d.Photo4d(project_path="point to project folder /Project")

# Algorithm to sort images in triplets, and create the reference table with sets :date, valid set, image names
myproj.sort_picture()

# Algorithm to check picture quality (exposure and blurriness)
myproj.check_picture_quality()

############################################################
## Part 2: Estimate camera orientation

# Compute camera orientation using the timeSIFT method:
myproj.timeSIFT_orientation()

# Convert a text file containing the GCP coordinates to the proper format (.xml) for Micmac
myproj.prepare_gcp_files(path_to_GCP_file, file_format="N_X_Y_Z")

# Select a set to input GCPs
myproj.set_selected_set("DSC02728.JPG")

# Input GCPs in 3 steps
# first select 3 to five GCPs to pre-orient the images
myproj.pick_initial_gcps()

# Apply transformation based on the few GCPs previously picked
myproj.compute_transform()

# Pick additionnal GCPs, that are now pre-estimated
myproj.pick_all_gcps()

############################################################
## Part2, optional: pick GCPs on extre image set
## If you need to pick GCPs on another set of images, change selected set (this can be repeated n times):
#myproj.compute_transform()
#myproj.set_selected_set("DSC02871.JPG")
#myproj.pick_all_gcps()

# Compute final transform using all picked GCPs
myproj.compute_transform(doCampari=True)

## FUNCTION TO CHANGE FOR TIMESIFT
# myproj.create_mask() #To be finished

############################################################
## Part3: Compute point clouds

# Compute point cloud, correlation matrix, and depth matrix for each set of image
myproj.process_all_timesteps()

# Clean (remove) the temporary working direction
myproj.clean_up_tmp()

Ressources

• Micmac: http://micmac.ensg.eu/index.php/Accueil
• Image processing images: skimage, openCV, Pillow
• python package to read exif data: https://pip.pypa.io/en/latest/user_guide/

Development

Message us to be added as a contributor, then if you can also modify the code to your own convenience with the following steps:

To work on a development version and keep using the latest change install it with the following

git clone [e-mail]:ArcticSnow/photo4D.git
pip install -e [path2folder/photo4D]

and to upload latest change to Pypi.org, simply:

1. change the version number in the file photo4d/__version__.py
2. run from a terminal from the photo4D folder, given your $HOME/.pyc is correctly set:

python setup.py upload