How to get the highest dominant color from google cloud vision api in python?

I have a list of .jpg images and i am trying to extract the dominant color from google cloud vision API - https://cloud.google.com/vision/docs/drag-and-drop

The below piece of function sometimes extracts the correct RGB values but sometimes it extracts incorrect RGB values as well. What should i change in the below code so that it always picks the dominant color with highest RGB percentage. i.e the first RGB value from the left.

def dominat_color(image):
    response = client.image_properties(image=image)
    props = response.image_properties_annotation

    max_frac=0.0
    #print('Properties:', props.dominant_colors.colors[0].red,",",props.dominant_colors.colors[0].green,",",props.dominant_colors.colors[0].blue,",",dominant_colors.colors[0].pixel_fraction)

    for color in props.dominant_colors.colors:

        var1=float(color.pixel_fraction)*100
    #var1=float(color.percent)

        if (var1 > max_frac):
            max_frac=var1
            var2=int(color.color.red)
            var3=int(color.color.green)
            var4=int(color.color.blue)
            #print("\nRGB: ", var2,",",var3,",",var4,",", (var1))


    if response.error.message:
        raise Exception(
            '{}\nFor more info on error messages, check: '
            'https://cloud.google.com/apis/design/errors'.format(
                response.error.message))
    return var2,var3,var4

creds = service_account.Credentials.from_service_account_file(r'xxxx.json') #credentials
client = vision.ImageAnnotatorClient(credentials=creds,)

Sample Output:

Image_name   Red   Green  Blue

k1.jpg       240   125     16

The red,green and blue values should be the left most RGB values in gcp --> https://cloud.google.com/vision/docs/drag-and-drop under properties tab i am just trying to extract the first RGB values from the left.

For your requirement, you can use a list in python to store the values and find the dominant value from the left. You can check the below sample code which you can use for your use case.

Code :

def dominat_color(image):
    from google.cloud import vision
    import io
    client = vision.ImageAnnotatorClient()

    image_uri = image
    image = vision.Image() # Py2+3 if hasattr(vision, 'Image') else vision.types.Image()
    image.source.image_uri = image_uri

    response = client.image_properties(image=image)
    props = response.image_properties_annotation
    
    
    #print('Properties:', props.dominant_colors.colors[0].red,",",props.dominant_colors.colors[0].green,",",props.dominant_colors.colors[0].blue,",",dominant_colors.colors[0].pixel_fraction)
    max_frac=0.0
    lst = []
    for color in props.dominant_colors.colors:

        var1=float(color.pixel_fraction)*100
        if (var1 > max_frac):
            max_frac = var1
                
            var2=int(color.color.red)
            lst.append(var2)
            var3=int(color.color.green)
            lst.append(var3)
            var4=int(color.color.blue)
            lst.append(var4)

    rmax = max(lst)
    index = lst.index(rmax)
    print(lst[index],lst[index+1],lst[index+2])
    
    
    if response.error.message:
        raise Exception(
            '{}\nFor more info on error messages, check: '
            'https://cloud.google.com/apis/design/errors'.format(
                response.error.message))
        
dominat_color(image_path)

Output :