Nora lighting

The main EMVA1288 processing code is divided into 6 parts. In the package, there is also a DatasetGenerator class that can generate automatically a set of data that can be analysed. The data are generated with a Camera simulator that can be run as a stand-alone object.

Kichler lighting

First, there is the info_marketing() function. This is a function that returns a dictionary to fill with the marketing data needed for the report.

Second, there is the info_op() function. This function returns a dictionary serving as a place holder for all the data needed for an operation point in the report

An EMVA1288 descriptor file is a file that contains the description of an EMVA1288 test including exposure times, photon count and corresponding images relative path to the descriptor.

Hinkley lighting

This class takes a dictionary (product of a ParseEmvaDescriptorFile object). It loads the related images and reduce it’s data to the minimum possible, preserving all relevant image data in as integers. The resulting data is a Python dictionary.

This class takes a Results1288 object and produces all the plots needed to create a reference datasheet of the EMVA1288 test

Access lighting

To use the code, you need to have a set of images that correspond to an EMVA1288 test. There are some sample image sets provided by the standard development group. Example datasets.

This class takes a dictionary with image data (product of a LoadImageData object), and transforms it into data that can be used for the EMVA1288 computations. It is important to note, that this is separate from LoadImageData because this step produces float values that are not easily transportable (db, json, etc…) without losing accuracy.