Digital Negative (DNG) file support

Abierto
  • ¿Algo no está bien?
#59 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Nueva funcionalidad
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
cpp, python
Área
computer-vision

Línea de trabajo

Start by reading the DNG specification linked in the issue and tracing how nvImageCodec handles the shown Python file-reading example. Identify the codec entry point and what DNG decoding requires; the issue does not name relevant source files or tests. Done means DNG files can be transcoded with GPU acceleration and the reported error is resolved.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

enhancement
Is this a new feature, an improvement, or a change to existing functionality?

New Feature

How would you describe the priority of this feature request

Nice to have (e.g. Adoption is possible, the feature will enhance the use-case even more).

Please provide a clear description of problem this feature solves

Could nvImageCodec support Digital Negative (DNG) files?

DNG is a standard format for camera raw files, the latter which capture unprocessed or minimally processed data directly from the camera sensor.

The standard's specification can be found here

Feature Description

As a software engineer, I would like to be able to have GPU acceleration for .dng image transcoding so that I can include these images into my computer-vision/machine-learning frameworks.

Describe your ideal solution

with open("my_dng_file.dng", "rb") as in_file:
data = in_file.read()

At present, this code errors with cuDevicePrimaryCtxRelease failed: 4

Describe any alternatives you have considered

I have looked into the rawpy library, but it does not provide GPU acceleration.

Additional context

I would be keen to investigate a solution to this problem if someone could point me towards an "entry point" :)

Check for duplicates
  • I have searched the open bugs/issues and have found no duplicates for this bug report
Lenguaje dominante
Jupyter Notebook
Estrellas
164
Forks
26
Merge medio
27 min
PR fusionados (30 d)
1

Preparar el entorno

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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