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Semantic Segmentation on Videos

A realtime frame-by-frame segmentation on user-given video input.

Model Used

Deeplabv3-MobileNetV3-Large is constructed by a Deeplabv3 model using the MobileNetV3 large backbone. The pre-trained model has been trained on a subset of COCO train2017, on the 20 categories that are present in the Pascal VOC dataset.

The accuracies of the pre-trained model evaluated on COCO val2017 dataset are listed below.

Model structure	              Mean IOU	Global Pixelwise Accuracy
deeplabv3_mobilenet_v3_large	  60.3	          91.2

🛠️Tech Stack

-OpenCV

-PyTorch

-ONNX

-Tensorflow Lite

-Python

-Version Control: Git & GitHub

Installation on Local System

Clone the repository

git clone https://github.com/vivupadi/Segmentation_app.git

cd Segmentation_app/src

Create virtual environment

python -m venv venv

source venv/bin/activate # On Windows: venv\Scripts\activate

Install dependencies

pip install -r requirements.txt

Run the Application

python load_model.py

Model architecture

Inference on CPU

til

Quantization

Quantized model(float 16) inference on local system

til

Quantized model(float 16) inference on Raspberry Pi 4

Future Plans

Reduce model to segment only Humans

Inference on Raspberry Pi 4 + Camera module

Structure of Pipeline

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

⭐ Star this repo if you find it helpful!

Made with ❤️ by Vivek Padayattil

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