PV-Drone-Inspect | photovoltaics modules from IR drone videos

by LukasBommes Jupyter Notebook Version: v0.0.1 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions Vulnerabilities Install Support

kandi X-RAY | PV-Drone-Inspect Summary

PV-Drone-Inspect is a Jupyter Notebook library. PV-Drone-Inspect has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

This software is written by Lukas Bommes, M.Sc. - Helmholtz Institute Erlangen-Nürnberg for Renewable Energy (HI ERN).

Support

Quality

Security

License

Reuse

Support

PV-Drone-Inspect has a low active ecosystem.

It has 5 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

PV-Drone-Inspect has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of PV-Drone-Inspect is v0.0.1

Quality

PV-Drone-Inspect has no bugs reported.

Security

PV-Drone-Inspect has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

PV-Drone-Inspect is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

PV-Drone-Inspect releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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PV-Drone-Inspect Key Features

No Key Features are available at this moment for PV-Drone-Inspect.

PV-Drone-Inspect Examples and Code Snippets

PV Drone Inspect,4 Usage,Step 3: Create config file

Jupyter Notebook

Lines of Code : 56

License : Permissive (MIT)

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---
plant_name: Plant A
work_dir: /storage-2/pvextractor-georeferencing/Plant_A/workdir
video_dir: /storage-2/pvextractor-georeferencing/Plant_A/
groups:
- name: Sector_1
  video_fps: 8.0
  row_orientation: horizontal
  cam_params_dir: calibration/ca

PV Drone Inspect,5 Output directory structure

Jupyter Notebook

Lines of Code : 49

License : Permissive (MIT)

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/workdir
  |-- splitted
  |    |-- timestamps.csv
  |    |-- gps
  |    |     |-- gps.csv
  |    |     |-- gps.json
  |    |     |-- gps.kml
  |    |-- preview
  |    |     |-- frame_000000.jpg
  |    |     |-- frame_000001.jpg
  |    |     |-- ...

PV Drone Inspect,4 Usage,Step 1: Run Docker image

Jupyter Notebook

Lines of Code : 12

License : Permissive (MIT)

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xhost +

sudo docker run -it \
    --ipc=host \
    --env="DISPLAY" \
    --gpus=all \
    -v /tmp/.X11-unix:/tmp/.X11-unix:rw \
    -v "$(pwd)":/pvextractor \
    -v /storage:/storage \
    -p "8888:8888" \
    pvextractor-geo \
    bash

chmod +x d

Community Discussions

No Community Discussions are available at this moment for PV-Drone-Inspect.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install PV-Drone-Inspect

To run PV Drone Inspect you need a machine running Ubuntu 18.04 LTS / 20.04 LTS and a Nvidia CUDA-compatible GPU with the latest Nvidia drivers installed. Furthermore, you need to install Docker CE and the Nvidia container toolkit.
The tool uses a pretrained Mask R-CNN for PV module detection. Download the pretrained Mask R-CNN model weights from here, extract the zip archive and place the folder "pv_modules20210521T1611" under extractor/segmentation/Mask_RCNN/logs. The resulting directory structure should look like follows:.
We user Docker to provide a consistent environment for the execution of PV Drone Inspect. When building the provided Docker image all required dependencies, e.g., Python, CUDA, Tensorflow, and OpenSfM, are installed and configured automatically. There are two ways to use the Docker image: A) building the image from the provided Dockerfile, or B) load a prebuilt image. Note, that you need to build/load the image only once. Afterwards, you can run the Docker image as specified in the usage section. To build the Docker image from the provided Dockerfile run the following command from the root directory of PV Drone Inspect. Alternatively, you can download a prebuilt Docker image from here. Place the tar archive in the project's root directory an load the Docker image by executing. Note, that the image was built on a machine with Ubuntu 20.04 LTS. Transferability to other operating systems is not guaranteed. If you run into issue with the prebuild image, please build the image from source as specified above.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: