Capstone Project

>> fish fish facts! <<

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The Project:

Dive in to fish out the facts!

A classification app for your holiday snapshots or your greatest catch. Raising awareness for species conservation.

Upload your fish image and use our Streamlit App, developed using Convolutional Neural Network & Transfer Learning. With this app you will find out all of the facts about your fish.

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Source of the data:

Kaggle Dataset owned by Sripaad Srinivasan. This fish species dataset, currently consisting of 3,960 images collected from 468 species, contains real-world images of fish captured in 3 conditions defined as

1. "controlled",
2. "out-of-the-water" and
3. "in-situ".

The "controlled", images consists of fish specimens, with their fins spread, taken against a constant background with controlled illumination.

The "in-situ" images are underwater images of fish in their natural habitat and so there is no control over background or illumination.

The "out-of-the-water" images consist of fish specimens, taken out of the water with a varying background and limited control over the illumination conditions.

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Team:

• Erik Gebel: GitHub & LinkedIn
• Karine Real: GitHub & LinkedIn
• Niels Lory: GitHub & LinkedIn

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Files of the Project:

1. Model Maker Notebook
2. Streamlit App Repo
3. Notebooks of the project
4. Presentation Slides
5. Team Logo

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Requirements and Environment

Requirements:

• pyenv with Python: 3.9.8

Environment:

You can use the following commands to set up the virtual environment:

pyenv local 3.9.8
python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt