Lambda-School-Labs/Labs26-StorySquad-DS-TeamB

# Connect to Google Cloud Vision API and utilize their safe_search to
# moderate illustration submissions

from google.cloud import vision
import io


def detect_safe_search(path):
    """
    Detects adult, violent or racy content in uploaded images
        Input: path to the image file
        Output: String, either stating 'No inappropriate material detected'
            or 'Image Flagged' with information about what is inappropriate
    """

    client = vision.ImageAnnotatorClient()

    # If local illustration
    with io.open(path, "rb") as image_file:
        content = image_file.read()
    image = vision.types.Image(content=content)

    # # If remote illustration
    # image = vision.types.Image()
    # image.source.image_uri = uri

    response = client.safe_search_detection(image=image)
    safe = response.safe_search_annotation

    # Names of likelihood from google.cloud.vision.enums
    likelihood_name = (
        "UNKNOWN",
        "VERY_UNLIKELY",
        "UNLIKELY",
        "POSSIBLE",
        "LIKELY",
        "VERY_LIKELY",
    )

    # Check illustration against each safe_search category
    # Flag if inappropriate material is 'Possible' or above
    if safe.adult > 2 or safe.violence > 2 or safe.racy > 2:
        # Set flag - provide information about what is inappropriate
        flagged = [
            ("adult: {}".format(likelihood_name[safe.adult])),
            ("violence: {}".format(likelihood_name[safe.violence])),
            ("racy: {}".format(likelihood_name[safe.racy])),
        ]
        return f"Image Flagged: {flagged}"

    else:
        return "No inappropriate material detected"