cv_project

Computer Vision Project

Elbrus Bootcamp | Phase-2 | Team Project

🦸‍♂️ Team

1. Salman Chakaev
2. Vladislav Filippov

🎯 Task

Create a service for object detection with YOLOv5 and image denoising using a custom AutoEncoder class.

🪜 Contents

1. Pizza ingredient detection using YOLOv5
2. Brain tumor detection from photographs using YOLOv5
3. Document denoising using an autoencoder

🌐 Deployment

The service is implemented on Streamlit

📚 Libraries

import torch
import PIL
import requests
import torch.nn as nn

from PIL import Image
from io import BytesIO
from torchvision import transforms

📚 Guide

How to run locally?

1. To create a Python virtual environment for running the code, enter:

   python3 -m venv my-env.

2. Activate the new environment:

   • Windows: my-env\Scripts\activate.bat
   • macOS and Linux: source my-env/bin/activate

3. Install all dependencies from the requirements.txt file:

   pip install -r requirements.txt..

UPD. In the future, galaxy segmentation from telescope photos using the Mask R-CNN model will be added.