generate-photo-metadata-csv

Before You Continue: Consider the PhotoTag.ai Lightroom Plug-In

Since this blog post was published, PhotoTag.ai launched a custom Lightroom Plug-In, simplifying the process of generating metadata for your photos. Download the PhotoTag.ai Lightroom Plug-In for free by clicking here.

Step 1: Creating an Account with PhotoTag.ai and Generating an API Token

To get started, head over to PhotoTag.ai’s API page and create an account. After signing up, you will receive 10 free upload credits, which you can use to generate automated keywords, titles, and descriptions for your images. If you need more credits, you can easily purchase additional ones within your PhotoTag.ai account.

Disclaimer: The uploaded files are only used to generate the keywords, title, and description at the time of upload. The original files are not saved or used for any other purpose. Only a low-resolution version of the file is saved so that you can see it in the album editor at PhotoTag.ai.

Step 2: Setting Up Python to Generate Your Photo Metadata CSV

Before diving into Lightroom, you'll need to generate a CSV file with your photos' metadata. A handy Python script available on GitHub makes this task straightforward. Here's how to get started:

Installing Python

If you don't have Python installed on your computer, you'll need to install it first. Visit the official Python website and download the latest version for your operating system. Follow the installation instructions, making sure to add Python to your system's PATH if prompted.

Running the Python Script

Once Python is installed, you'll want to download the script that generates the CSV file. You can find the script at this GitHub repository.

1. Click on the link to view the script.
2. Right-click on the page and select "Save As" to download the .py file to your computer.
3. Open your command line or terminal, navigate to the directory where you saved the script, and run the following command:

python generate-photo-metadata-csv.py

This script will prompt you for the location of your photo library and then generate a CSV file containing the titles, descriptions, and keywords for all the photos.

Step 3: Importing Your CSV into Adobe Lightroom

Adobe Lightroom does not natively support importing metadata from CSV files. To bridge this gap, we'll use a third-party plugin called LR/Transporter.

Installing and Configuring LR/Transporter

1. Download and install LR/Transporter from its official website or Adobe's plugin directory.
2. Follow the plugin's installation instructions closely.
3. Once installed, open Lightroom and go to the Plugin Manager to configure LR/Transporter to recognize your CSV format.

Importing Photos into Lightroom

Before importing metadata, make sure your photos are already imported into Lightroom. It's crucial that the filenames in your CSV match exactly with those in your Lightroom library for the metadata to link correctly.

Importing Metadata from the CSV File

1. Open the LR/Transporter import window through Lightroom's Plugin Manager.
2. Select your CSV file generated by the Python script.
3. Match the metadata fields from your CSV with the corresponding fields in Lightroom.
4. Execute the import. The plugin will process the CSV file and apply the metadata to your photos in Lightroom.

Step 4: Verification and Adjustment

After the import process is complete, it's essential to verify that the metadata has been applied correctly. Select a photo and check its metadata panel to ensure accuracy. If you find any discrepancies, you can manually adjust the metadata within Lightroom.

Conclusion

By leveraging a Python script and a Lightroom plugin, photographers can significantly streamline the process of managing photo metadata. This combination allows for the efficient organization, tagging, and managing of large photo libraries, making the photographer's workflow more manageable and time-efficient.

Remember to visit the GitHub repository to download the Python script and start organizing your photo library more effectively today.