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TouchToVision project for the Computer Vision course 2023/24

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TouchToVision

TouchToVision project for the Computer Vision course 2023/24

Description

The project is about the development of a system which able to pair a visual frame with a tactile frame. The dataset used for the project is a subset of the original TouchAndGo dataset. The proposed pipeline is able to extract from the visual video and tactile video the most relevant frames and then pair them.

Dataset

The dataset is composed of 4 objects sampled from the TouchAndGo dataset. The processed object are saved in the dataset folder. The dataset is composed of 4 objects: rock, rock2, tree, grass. Each object is composed divided in 2 folders, one for the visual frames and one for the tactile frames

Repository structure

The repository is structured as follows:

  • data: folder containing the dataset
  • src: folder containing scripts used to test monocular depth estimation models
  • weights: folder containing the weights of the super resolution model Real-ESRGAN
  • sampler.py: script used to sample the visual and tactile frames from the dataset
  • matcher.py: script used to match the visual and tactile frames once they have been sampled using the sampler

Usage

First, create a virtual environment and install the required packages:

pip install -r requirements.txt

Then, run the sampler script to sample other frames from the dataset (you can already find the sampled frames in the data folder):

python sampler.py -i rock 

Finally, run the matcher script to match the visual and tactile frames among different objects:

python matcher.py --class rock

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TouchToVision project for the Computer Vision course 2023/24

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