Add files via upload

README.md

@@ -1,2 +1,48 @@
-# py-denseflow
-extract TVL1 optical flows in python
+# Py-denseflow
+
+
+This is a python port of denseflow, which extract the videos' frames and **optical flow images** with ==TVL1 algorithm== as default.
+
+---
+
+### Requirements:
+- numpy
+- cv2
+- PIL.Image
+- multiprocess
+- scikit-video (optional)
+- scipy
+
+## Installation
+#### Install the requirements:
+```
+pip install -r requirements.txt
+
+```
+
+---
+
+## Usage
+The denseflow.py contains two modes including '**run**' and '**debug**'.
+
+
+here 'debug' is built for debugging the video paths and video-read methods. (IPython.embed suggested)
+
+Just simply run the following code:
+
+```
+python denseflow.py --new_dir=denseflow_py --num_workers=4 --step=1 --bound=20 --mode=debug
+
+```
+While in 'run' mode, here we provide multi-process as well as multi-server with manually s_/e_ IDs setting.
+
+for example:  server 0 need to process 3000 videos with 4 processes parallelly working:
+
+```
+python denseflow.py --new_dir=denseflow_py --num_workers=4 --step=1 --bound=20 --mode=run --s_=0 --e_=3000
+```
+
+---
+
+Just feel free to ask me if any bugs exist.
+

requirements.txt

@@ -0,0 +1,4 @@
+numpy
+sk-video
+scipy
+multiprocess