YoloV3 Fire Detection model! (GPU ENABLED)

A Project on Fire detection using YOLOv3 model. This repo consists of code used for training and detecting Fire using custom YoloV3 model. I trained my custom detector on existing yolov3 weights trained to detect 80 classes.

The Dataset is collected from google images using Download All Images chrome extension. I labelled dataset using Label Img.

Some of the readily labelled datasets are available here @Google's Open Image Dataset v5.

🧾 Colab Notebook	📂 Dataset with Labels	🔑 Trained Model	✍ LabelImg
	Dataset with Labels	Download Model	Label Img

🧬 Sample outputs from Custom YOLOv3 model

Input	Output

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📈 Training Performance Chart

Here is the chart to describe how my performed during entire training process. It shows average loss vs. iterations. For a model to be 'accurate' you would aim for a loss under 2.

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📂 Files Required :

• Darknet repository
• Labeled Custom Dataset
• Custom .cfg file
• obj.data and obj.names files
• train.txt file (test.txt is optional here as well)

I referenced this tutorial from an YouTube Video by TheAIGuy channel. You can follow a step-by-step walkthrough of video and the code here: https://www.youtube.com/watch?v=10joRJt39Ns

You can download the yolov3 pretrained weights by clicking here and yolov3-tiny here

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⚡ Colab Hack: ⭐

If you are a student like me, and unable to pay such amount, here is a jugad for you. 😉

👉Step 1: In colab notebook, type CTRL + SHIFT + I (Inspect element)
👉Step 2: Go to the console tab and paste the code given in the image below.

function ClickConnect(){
console.log("Working");
document.querySelector("colab-toolbar-button#connect").click()
}
setInterval(ClickConnect,60000)

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🧠 Further Ideas

• Integrate the model with IOT and leverage Cloud services for real-time monitoring and alerting system.

Any Ideas/suggestions/contributions are highly appreciable.