https://github.com/sreeeswaran/image-classification-using-efficientnet
This project uses a pre-trained EfficientNet model to classify images into different categories. The model is fine-tuned on a custom dataset for this purpose.
https://github.com/sreeeswaran/image-classification-using-efficientnet
deep-learning efficientnet efficientnet-keras efficientnet-pytorch image-classification image-classification-using-efficientnet
Last synced: 11 months ago
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This project uses a pre-trained EfficientNet model to classify images into different categories. The model is fine-tuned on a custom dataset for this purpose.
- Host: GitHub
- URL: https://github.com/sreeeswaran/image-classification-using-efficientnet
- Owner: SreeEswaran
- License: apache-2.0
- Created: 2024-06-21T17:58:55.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-09T16:54:56.000Z (over 1 year ago)
- Last Synced: 2025-01-22T23:25:25.661Z (about 1 year ago)
- Topics: deep-learning, efficientnet, efficientnet-keras, efficientnet-pytorch, image-classification, image-classification-using-efficientnet
- Language: Jupyter Notebook
- Homepage:
- Size: 25.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Image-Classification-using-EfficientNet
This project uses a pre-trained EfficientNet model to classify images into different categories. The model is fine-tuned on a custom dataset for this purpose.
### Note:
- I added a new section under "Data" specifically for the ImageNet dataset.
- Provided a link to the ImageNet download page. Users will need to register and follow the instructions on the ImageNet website to download the dataset.
- Emphasized the need to organize the downloaded dataset into `train` and `test` folders within the `data` directory of your project.
## Data
### ImageNet Dataset
You can download the ImageNet dataset using the following links:
- [ImageNet Download (Registration Required)](http://www.image-net.org/download)
After downloading, extract the dataset and organize it into `train` and `test` folders as per your project's data structure.
## Setup
1. Clone the repository:
```bash
git clone https://github.com/SreeEswaran/Image-Classification-using-EfficientNet.git
cd Image-Classification-using-EfficientNet
```
2. Install the dependencies
```bash
pip install -r requirements.txt
```
3. Training the model
```bash
python scripts/train.py
```
4. Evaluating the model
```bash
python scripts/evaluate.py
```
5. Making predictions
```bash
python scripts/predict.py
```