iraadit

# Interpolate video frames for a higher frame rate
ffmpeg -i source.mp4 -filter:v minterpolate -r 25 result.mp4
ffmpeg -i source.mp4 -vf minterpolate=50,tblend=all_mode=average,framestep=2 result.mp4

# Crop a video to the bottom right quarter
ffmpeg -i in.mp4 -filter:v "crop=in_w/2:in_h/2:in_w/2:in_h/2" -c:a copy out.mp4

# Resize a video to half size
ffmpeg -i input.mkv -filter_complex "scale=in_w/2:in_h/2" output.mkv

iraadit

CC = g++
CFLAGS = -g -Wall
SRCS = HelloWorld.cpp
PROG = HelloWorld

OPENCV = `pkg-config opencv --cflags --libs`
LIBS = $(OPENCV)

$(PROG):$(SRCS)
	$(CC) $(CFLAGS) -o $(PROG) $(SRCS) $(LIBS)

iraadit

#!/bin/bash

NOW=$(date "+%Y-%m-%d")
mkdir $HOME/tmp/envs-$NOW
ENVS=$(conda env list | grep '^\w' | cut -d' ' -f1)
for env in $ENVS; do
    source activate $env
    conda env export > $HOME/tmp/envs-$NOW/$env.yml
    echo "Exporting $env"
done

iraadit

Bulk Downloading With The Ability to Specify Individual Filenames

After a few hours of searching, I've finally found a convenient way to download a large amount of files in a bulk/multi-threaded/parallel manner, while still having the ability to specify the saved files' names.

Many thanks to Diego Torres Milano

The input file (dl_data.txt):

bird_4345_543.jpg https://example.com/pictures/5351/image.jpg
bird_4345_544.jpg https://example.com/5352/pictures/image.jpg

iraadit

Export Class Images from PascalVOC Annotations

This script reads PascalVOC xml files, and crops the class instances into seperate image files.

Note: This script relies on ImageMagick for the crop (convert) functionality. It comes pre-installed on most recent versions of Ubuntu.

Disclaimer: This code is a modified version of Dat Tran's xml_to_csv.py

Example:

Let's say we have this image in our train folder:

iraadit

Convert PascalVOC Annotations to YOLO

This script reads PascalVOC xml files, and converts them to YOLO txt files.

Note: This script was written and tested on Ubuntu. YMMV on other OS's.

Disclaimer: This code is a modified version of Joseph Redmon's voc_label.py

Instructions:

1. Place the convert_voc_to_yolo.py file into your data folder.

iraadit

047d20b52defb3c86ecf1ddf2e84ae8847d18abfde3e3542b4a0a1f11b6f12614778fe3399a95e951ac367c6a9daf56a1cd93880504d47c487a50e1a0f2623c936

iraadit

# Download installers
mkdir ~/Downloads/nvidia
cd ~/Downloads/nvidia
wget https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run
wget http://us.download.nvidia.com/XFree86/Linux-x86_64/384.59/NVIDIA-Linux-x86_64-384.59.run
sudo chmod +x NVIDIA-Linux-x86_64-384.59.run
sudo chmod +x cuda_8.0.61_375.26_linux-run
./cuda_8.0.61_375.26_linux-run -extract=~/Downloads/nvidia/
# Uninstall old stuff
sudo apt-get --purge remove nvidia-*

iraadit

ffmpeg -i shame-run.mov -r 24/1 test/output%03d.jpg

iraadit

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites