Y_Stub

This directory is a very basic individual approach to the state of the art object detection algorithm YOLO based image tagger. For more information about YOLO please refer Here.

Installation

Clone and install requirements

$ git clone https://github.com/13idyut/Y_Stub.git
$ cd Y_Stub
$ pip install -r requirements.txt

Download pretrained weights

Download pretrained YOLOv3 weights from Here or just run:

$ cd Y_Stub
$ wget https://pjreddie.com/media/files/yolov3.weights

Inference

Uses pretrained weights to generate stubs from the image. Stubs are stored in tag.txt. A paragraph is generated out of the stubs and stored in answer.txt. One can customise paragraph template as per their need to generate description out of Y_stub. To see Y_Stub in action just run:

$ cd Y_Stub
$ python app.py path/to/image/<image-name.jpg/png>

Credit

YOLOv3: An Incremental Improvement

Joseph Redmon, Ali Farhadi

Y_Stub is based on YOLOv3 implemented in TensorFlow. Here iou threshold is set to 0.5 and confidence threshold is set to 0.7. User can tweak vales as per their need.

[paper][website][YOLO]

License

MIT