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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.

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SreeEswaran/Image-Classification-using-EfficientNet

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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:

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:
git clone https://github.com/SreeEswaran/Image-Classification-using-EfficientNet.git
cd Image-Classification-using-EfficientNet
  1. Install the dependencies
    pip install -r requirements.txt
  2. Training the model
    python scripts/train.py
  3. Evaluating the model
    python scripts/evaluate.py
  4. Making predictions
    python scripts/predict.py

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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.

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