todokku / cvplayground

A computer vision playground to try and test end to end(test to deploy) computer vision pipeline. Current app version is at https://cvplayground.herokuapp.com/

Computer Vision Playground

A computer vision playground to try and test end to end(test to deploy) computer vision pipeline.

To contribute create an issue and refer Contributing for possible options.

App 1 :

• Name : Process videos for object detection using Tensorflow

• Models currently supported* :

	DB Code	Model
1	ssdmv2i	ssd_mobilenet_v2_coco
2	ssdiv2	ssd_inception_v2_coco_2017_11_17 (Currently active)

• Database : SQLite

• UI based app version : https://cvplayground.herokuapp.com/

• Deployment ProcFile : added

• Languages, Tools, Frameworks : TensorFlow, Python, Flask, HTML+CSS+JS, SQLite database.

  Getting Started :

  • Check to see if the following structure exists else create the following directory structure :
  • The downloads folder will host all the processed files for sending the user to download and uploads for saving uploaded files.
  • The models folder is from the tensorflow models directory, you only need object detection folder from that.
  • codes has the main video object detection code.
  • db has the database sqlite file.
  • templates has the web HTML templates for user interaction.

  Installation :

  • Go inside the main project directory and execute

    pip install -r requirements.txt

    command to install all the necessary requirements needed to run this project.

  • Create a sqlite database file inside db giving the name you wish. The project uses cvplayground.sqlite for simplicity.

  • Execute the below create statement to create the necessary tables inside the databse created.

  CREATE TABLE "uploads" (
  "id"	TEXT UNIQUE,
  "status"	NUMERIC,
  "isUploaded"	INTEGER,
  "isProcessed"	INTEGER,
  "location"	TEXT,
  "datetime"	TEXT,
  "model_name"	TEXT
   )
  
  

  • Open a terminal and execute

    python flask_server.py

    which will start the default flask_server at localhost:5000 or whatever port you designate in the flask_server.py file.

  • You are now ready.

  Notes :

  More model support coming soon. Status passing, pytest with code 5. Import requires >tensorflow model folder inside codes directory, however if it is available in your path >then ou can directly link to it. More models can be downloaded and saved in detect_models, the model name needs to be >added in the dictionary and saved accordingly in the database to take effect. Heroku slug size exceeding due to packages and the model. The slug size limits deploying this on Heroku , hence deploying to follow on services >like AWS Beanstalk or Google app engine.