Time Code JS

Time code detection on a video frame. Detects 'xx:xx:xx:xx' and 'xx:xx:xx;xx' formats.
Runs in a web browser without backend.

Usage

``
npm install timecodejs
get ocr model dir "newocr.tf/"
`

`html


`

Build timecodeocr.js Plugin

`


Clone the repo

git clone https://github.com/videogorillas/timecodejs.git
cd timecodejs/

install node_modules/

make install

webpack src/*.js

make pack

Install dev http server

pip install rangehttpserver

Mount test data if needed

ln -s /GTS_Proxy_Source_examples/norm/ ./videos/norm

Start dev http server

python -m RangeHTTPServer

Open test HTML in your browser

open http://localhost:8000/test/test_bundle.html
`

Train OCR model

`
cd trainModel/

virtualenv -p python3.6 venv/
./venv/bin/activate
pip3 install -r ./requierments.txt
pip3

Prepare backgound images

find ~/train/coco/train2017/ -type f > ./bcgs.txt

Train char OCR

CUDA_VISIBLE_DEVICES=0 python newocr.py

Convert model to TF javascript

tensorflowjs_converter --input_format keras ./checkpoints/newocr2.hdf5 ../newocr.tf/

``

$3

- Go to HAAR training home

cd ./haar/

- Create positive samples list

unzip cuts.zip
find cuts/ -type f > positives.txt

- Create negative samples list

mkdir negs/
ln -s /mnt/coco/train2017/ ./negs/train2017
find negs/ -type f > negs/negatives.txt

- Create opencv VEC file from positives and negs

./create_samples.sh > haar.log 2>&1
python ./mergevec.py -v ./samples_v6/cuts/ -o samples_v6.vec

- Train cascade

mkdir cascade_v6/
./train_cascade.sh

- Validate cascade

python check_cascade.py ./cascade_v6/cascade.xml