🐕 Stray Dogs Detection System 🐕

I. Introduction

Motivation

High population of stray dogs in Karachi leading to safety concerns and conflicts between humans and stray dogs.

Objective

Develop a stray dog detection model to identify and locate stray dogs across the city.

Solution

Create a system using AI and object detection to detect stray dogs and provide their location to authorities.

Benefits

Efficiently capture stray dogs, enabling authorities to sterilize and vaccinate them, reducing fear and promoting harmony between humans and stray dogs.

II. The Dataset

Find the raw data at Drive-link
Find the pre-processed dataset at Drive-link

III. Model Training

Download the pre-processed dataset from the drive link
Upload it on Colab, or your own Drive.
If you uploaded it on Drive, then mount your Google Drive in your Colab file, else just upload the dataset's zip file on Colab (it might take some time).
Unzip the file using:
```
 !unzip <path_to_dataset.zip_file>
```

Clone Yolov5's GitHub, cd to yolov5 and install the requirements using:

!git clone https://github.com/ultralytics/yolov5
%cd yolov5
%pip install -r requirements.txt

Upload yolo5s.pt and custom_dataset.yaml on your Colab

Train your own model using the command:

!python train.py --img 640 --cfg /content/yolov5/models/yolov5m.yaml --hyp /content/yolov5/data/hyps/hyp.scratch-med.yaml --batch 32 --epochs 50 --data /content/custom_dataset.yaml --weights /content/yolov5s.pt  --workers 24

I trained for 100 epochs initially but 90 epochs gave the best result.

Save the trained model. You can find it at /contents/yolov5/runs/train/exp/weights/best.pt
The trained model is the best.pt file in this repo, but you can also find it at Drive-link

Apply object detection on a video/image file using:

!python detect.py --img 640 --source <path_to_source_file> --conf 0.5 --weights /content/yolov5/runs/train/exp/weights/best.pt

Reminder: you can just use some other dataset, or change the parameters as per your preference to train your own custom object detection model :))

IV. Model Deployment Setup

This project might only work on your system if you have a GPU (else it will only work for image files and not the video ones)
You can replace the best.pt file with your own custom object detection model.

cmd:

 cd <path_to_your_fav_directory>

git clone https://github.com/tselane2110/stray-dogs-detection-system

cd <path_to_the_cloned_repository>

create 4 folders in static\ :
- images
- predicted_images
- videos
- predicted_videos
create a virtual environment by executing the following command in your cmd
```
python -m venv virtual
```
activate the virtual environment by executing the following command in your cmd
```
virtual\Scripts\Activate.ps1
```
install the required libaries by executing the following command in your cmd
```
pip install -r requirements.txt
```
run the following command in your cmd
```
python main-app.py
```
go to 192.168.1.101:5000 on your browser
choose a file then upload it
that's it for now, have fun!

Note: This is an ongoing project, so Ill be updating it from time to time
Also, if you encounter any issue, kindly do let me know so I can fix it!