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https://github.com/adesoji1/image-organization-project-using-google-cloud-vision-api

automate the organization of images in our Google Drive. Our goal is to categorize and move images into specific folders based on their content.
https://github.com/adesoji1/image-organization-project-using-google-cloud-vision-api

googlevisionapi

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automate the organization of images in our Google Drive. Our goal is to categorize and move images into specific folders based on their content.

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README 

        
The automation process in this project involves using a Python script that performs the following steps automatically:



1. **Authenticate and Initialize Clients**: The script uses service account credentials to authenticate with the Google Cloud Vision API and Google Drive API.



2. **List Images**: It retrieves a list of image files from a specified Google Drive folder.



3. **Download Images**: The script downloads each image locally for analysis.



4. **Analyze Images**: It uses the Google Cloud Vision API to analyze the content of each image and retrieve labels/categories.



5. **Categorize and Move Images**: Based on the labels retrieved, the script determines the appropriate folder for each image and moves it to the corresponding folder in Google Drive.



Here is a more detailed breakdown of the automated steps:



### Script Details (`organize_images.py`)



```python

import os

import io

from google.cloud import vision

from google.oauth2 import service_account

from googleapiclient.discovery import build

from googleapiclient.http import MediaIoBaseDownload, MediaFileUpload

from config import KEY_PATH, SOURCE_FOLDER_ID, CATEGORIES_TO_FOLDERS



# Authenticate and initialize clients

credentials = service_account.Credentials.from_service_account_file(KEY_PATH)

vision_client = vision.ImageAnnotatorClient(credentials=credentials)

drive_service = build('drive', 'v3', credentials=credentials)



def list_images(folder_id):

    query = f"'{folder_id}' in parents and mimeType contains 'image/'"

    results = drive_service.files().list(q=query, fields="files(id, name)").execute()

    items = results.get('files', [])

    return items



def download_image(file_id, file_name):

    request = drive_service.files().get_media(fileId=file_id)

    fh = io.FileIO(file_name, 'wb')

    downloader = MediaIoBaseDownload(fh, request)

    done = False

    while done is False:

        status, done = downloader.next_chunk()

    return file_name



def upload_image(file_name, folder_id):

    file_metadata = {

        'name': file_name,

        'parents': [folder_id]

    }

    media = MediaFileUpload(file_name, resumable=True)

    file = drive_service.files().create(body=file_metadata, media_body=media, fields='id').execute()

    return file.get('id')



def analyze_image(file_name):

    with open(file_name, 'rb') as image_file:

        content = image_file.read()

    image = vision.Image(content=content)

    response = vision_client.label_detection(image=image)

    labels = response.label_annotations

    categories = [label.description for label in labels]

    return categories



def categorize_and_move_images(folder_id, categories_to_folders):

    images = list_images(folder_id)

    for image in images:

        file_id = image['id']

        file_name = image['name']

        local_path = download_image(file_id, file_name)

        categories = analyze_image(local_path)

        

        # Determine the target folder based on categories

        target_folder_id = None

        for category in categories:

            if category in categories_to_folders:

                target_folder_id = categories_to_folders[category]

                break

        

        if target_folder_id:

            upload_image(local_path, target_folder_id)

            drive_service.files().delete(fileId=file_id).execute()

        os.remove(local_path)



if __name__ == '__main__':

    categorize_and_move_images(SOURCE_FOLDER_ID, CATEGORIES_TO_FOLDERS)

```



### Configuration (`config.py`)



```python

# config.py

KEY_PATH = 'path/to/your/service-account-file.json'

SOURCE_FOLDER_ID = 'your_source_folder_id'

CATEGORIES_TO_FOLDERS = {

    'Cat': 'folder_id_for_cats',

    'Dog': 'folder_id_for_dogs',

    # Add more categories and corresponding folder IDs

}

```



### How the Automation Works:



1. **Authentication**: The script uses the service account credentials to authenticate with Google Cloud services.

2. **Image Listing**: It lists all images in the specified Google Drive folder.

3. **Downloading**: Each image is downloaded locally for processing.

4. **Analysis**: The Vision API is used to analyze the content of the image and obtain labels.

5. **Categorization**: The script matches the obtained labels with the predefined categories.

6. **Moving Images**: Based on the matched category, the image is uploaded to the corresponding folder in Google Drive, and the local copy is deleted.



To run this script, you simply execute:



```sh

python organize_images.py

```



This command triggers the entire workflow, handling the images in your Google Drive folder automatically according to the specified categories and folders.