https://github.com/sreeeswaran/object-detection-yolov5
This project demonstrates object detection using YOLOv5. The model is trained on a custom dataset and can detect objects in new images. YOLOv5 is a state-of-the-art object detection model known for its speed and accuracy, making it suitable for real-time applications.
https://github.com/sreeeswaran/object-detection-yolov5
object-detection object-detection-model object-detection-using-yolov5 yolo yolo-dataset yolov5
Last synced: 3 months ago
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This project demonstrates object detection using YOLOv5. The model is trained on a custom dataset and can detect objects in new images. YOLOv5 is a state-of-the-art object detection model known for its speed and accuracy, making it suitable for real-time applications.
- Host: GitHub
- URL: https://github.com/sreeeswaran/object-detection-yolov5
- Owner: SreeEswaran
- Created: 2024-07-14T15:49:03.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-12-16T16:57:01.000Z (6 months ago)
- Last Synced: 2025-01-22T23:25:26.460Z (5 months ago)
- Topics: object-detection, object-detection-model, object-detection-using-yolov5, yolo, yolo-dataset, yolov5
- Language: Python
- Homepage:
- Size: 20.5 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Object-Detection-YOLOv5
This project demonstrates object detection using YOLOv5. The model is trained on a custom dataset and can detect objects in new images. YOLOv5 is a state-of-the-art object detection model known for its speed and accuracy, making it suitable for real-time applications.
## Dataset
You can use any dataset that follows the YOLO format. For this project, we assume the dataset is organized as follows:
### Download Dataset
You can download a sample dataset from [Roboflow's Public Object Detection Datasets](https://public.roboflow.com/object-detection). Extract the dataset into the `data/` directory.
## Model Architecture
YOLOv5 is a convolutional neural network (CNN) designed for object detection. It divides the image into a grid and predicts bounding boxes and class probabilities for each grid cell.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/SreeEswaran/Object-Detection-YOLOv5.git
cd Object-Detection-YOLOv5
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Download and preprocess the dataset as described above.
## Usage
### Training
To train the model, run:
```bash
python scripts/train.py --config config.yaml
```
### To evaluate the model, run:
```bash
python scripts/evaluate.py --config config.yaml
```
### To infer, run
```bash
python scripts/infer.py --image_path path/to/your/image.jpg --model_path models/yolov5_model.pth
```