/Bounding_Box_Regression_TF

Explore Bounding Box Regression in Object Detection with TensorFlow.

Primary LanguagePython

Object Detection with Bounding Box Regression

The project demonstrates the working of the Bounding Box Regression technique used in object detection tasks. It can efficiently predict the four coordinates of a bounding box around the image with its class probabilities too.

View the article on Medium ~> Getting Started With Bounding Box Regression In TensorFlow

Check out the Google Colab notebook ~> https://colab.research.google.com/drive/1usT_XYE6DLENeUL3__GNCYAWn-0NbVh6#forceEdit=true&offline=true&sandboxMode=true

The following files are included in this repo:

  1. DataProcessor.py : Extract the images and XML annotations to convert them .npy files ready for training/testing.

  2. Model.py : Defines the CNN model and other useful methods.

  3. MainFile.py : Trains the model on the data.

  4. Evaluation.py : Loads a model from the given h5py file and predicts bounding boxes for various images, draws them on the image and then finally saves the images to a directory.

By default, the Evaluation.py file reads the pretrained model weights which are included with the repo.

Make sure you download the data first -> https://www.kaggle.com/mbkinaci/image-localization-dataset