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Fast Edge Detection Using Structured Forests

Team Members

Haard Panchal 201501153

Saurabh Ravindranath 201501159

Eashwar Subramanian 201501163

Running the code:

The code is run as follows "python main.py"

The input images are to be placed in the directory "./input/images/test/"

The output images will be saved to the directory "./edges/"

Training:

The model is to be trained using the full dataset available at the following link: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/BSR/BSR_bsds500.tgz

The dataset is to be placed in the "input" directory

Once the training is over, the model will be saved to "./model/forests/"

Currently only a part of the dataset is in the repository, due to space constraints

Examples:

Some of the outputs obtained when the model was trained on the full dataset is given in the "./examples" directory, where the inputs and corresponding outputs are in the directories "./examples/input" and "./examples/output" respectively.

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  • Python 100.0%