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@peter-moran
peter-moran / gstreamer_view.cpp
Last active June 9, 2022 18:44
Bare-bones C++ script for viewing gstreamer video from the CSI port of the Nvidia Jetson TX2.
/*
Example code for displaying gstreamer video from the CSI port of the Nvidia Jetson in OpenCV.
Created by Peter Moran on 7/29/17.
https://gist.github.com/peter-moran/742998d893cd013edf6d0c86cc86ff7f
*/
#include <opencv2/opencv.hpp>
std::string get_tegra_pipeline(int width, int height, int fps) {
return "nvcamerasrc ! video/x-raw(memory:NVMM), width=(int)" + std::to_string(width) + ", height=(int)" +
@peter-moran
peter-moran / gstreamer_fps_test.cpp
Last active October 8, 2021 04:22
Example code for displaying (and finding FPS of) gstreamer video in OpenCV.
/*
Example code for displaying (and finding FPS of) gstreamer video in OpenCV.
Created by Peter Moran on 7/29/17.
Usage
-------
After compiling, run this program with the following arguments. All are optional, but must be used cumulatively.
`./gstreamer_test <width> <height> <fps> <window_size> <display_video>`
For example, to display 1080p video at 30 fps and calculate the true fps over a 15 sample running window, run:
@fchollet
fchollet / classifier_from_little_data_script_2.py
Last active February 26, 2025 01:37
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@blackfalcon
blackfalcon / git-feature-workflow.md
Last active October 8, 2025 17:33
Git basics - a general workflow

Git-workflow vs feature branching

When working with Git, there are two prevailing workflows are Git workflow and feature branches. IMHO, being more of a subscriber to continuous integration, I feel that the feature branch workflow is better suited, and the focus of this article.

If you are new to Git and Git-workflows, I suggest reading the atlassian.com Git Workflow article in addition to this as there is more detail there than presented here.

I admit, using Bash in the command line with the standard configuration leaves a bit to be desired when it comes to awareness of state. A tool that I suggest using follows these instructions on setting up GIT Bash autocompletion. This tool will assist you to better visualize the state of a branc