https://github.com/fatimanasirawan/deep-learning-project

Project Demo
https://github.com/fatimanasirawan/deep-learning-project

deep-learning deep-learning-with-frontend deeplearning-ai image-classification semester-project

Last synced: 5 days ago
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Project Demo

• Host: GitHub
• URL: https://github.com/fatimanasirawan/deep-learning-project
• Owner: fatimanasirawan
• Created: 2024-06-04T08:11:37.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-06-11T15:43:10.000Z (5 months ago)
• Last Synced: 2024-06-11T23:14:12.955Z (5 months ago)
• Topics: deep-learning, deep-learning-with-frontend, deeplearning-ai, image-classification, semester-project
• Homepage: https://www.linkedin.com/posts/fatimanasirawan_deeplearning-softwareengineering-imageprediction-activity-7206323562926768128-O-EN?utm_source=share&utm_medium=member_desktop
• Size: 10.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Instructions to Run the Project

1. **Open Google Colab:**

   - Open [Google Colab](https://colab.research.google.com/).

2. **Upload and Run the `.ipynb` File:**

   - Upload your Jupyter notebook (`.ipynb` file) to Colab.

   - Paste the code into the notebook and run it to download the `.h5` trained data.

3. **Move `.h5` File to the Project Folder:**

   - Once the `.h5` file is downloaded, move it into the `Fatima's Model` folder.

4. **Set Up Visual Studio Code:**

   - Open Visual Studio Code (VS Code).

   - Open the project folder in VS Code.

5. **Install TensorFlow:**

   - Open a terminal in VS Code.

   - Install TensorFlow by running the following command:

     ```

     pip install tensorflow

     ```

6. **Run the Application:**

   - In the terminal, navigate to the project directory if you are not already there.

   - Run the application by typing:

     ```

     python app.py

     ```

Your code should now be running successfully.

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