import os
import gradio as gr
from services.aws_service import AwsService
from dotenv import load_dotenv
import cv2
import face_recognition
import numpy as np

load_dotenv()
   
def find_face_encodings(image):
    face_enc = face_recognition.face_encodings(image)
    return face_enc[0]

def face_similarity(img1, img2, compare_image_folder=""):
    image_1 = find_face_encodings(img1)
    image_2 = find_face_encodings(img2)

    # checking both images are same
    is_same = face_recognition.compare_faces([image_1], image_2)[0]
    accuracy = 0
    if is_same:
        # finding the distance level between images
        distance = face_recognition.face_distance([image_1], image_2)
        distance = round(distance[0] * 100)
    
        # calcuating accuracy level between images
        accuracy = 100 - round(distance)
    
    return {"is_same": "true" if is_same else "false", "accuracy": accuracy, "error": "false", "compare_image": compare_image_folder}

def convert_pil_to_open_cv(pil_image):
    open_cv_image = np.array(pil_image) 
    open_cv_image = open_cv_image[:, :, ::-1].copy() 
    return open_cv_image

def check_image_similarity(main_image_folder, compare_image_folder):
    main_image = AwsService.get_image_from_s3(os.environ.get('AWS_S3_BUCKET'), main_image_folder)
    compare_image = AwsService.get_image_from_s3(os.environ.get('AWS_S3_BUCKET'), compare_image_folder)

    result = False

    try:
        result = face_similarity(convert_pil_to_open_cv(main_image["pil"]), convert_pil_to_open_cv(compare_image["pil"]), compare_image_folder)
    except Exception as e:
        print("Error on execution: ", e)
    finally:
        if not result:
          result = {"is_same": "false", "accuracy": 0, "error": "true", "compare_image": compare_image_folder}

    return result

def compare_photoshoot_crops(photo_shoot_id, main_image_folder, compare_image_folder):
    if compare_image_folder == "":
        folder = "PhotoShoots/" + str(photo_shoot_id) + "/Croppeds"
        files = AwsService.get_files_from_s3(os.environ.get('AWS_S3_BUCKET'), folder)
        results = []
    
        for file in files:
            if main_image_folder != file['Key']:
                result = check_image_similarity(main_image_folder, file['Key'])
                results.append(result)

        return results
    else:
        return check_image_similarity(main_image_folder, compare_image_folder)
    
iface = gr.Interface(
    fn=compare_photoshoot_crops, 
    inputs=[
        gr.Textbox(lines=1, placeholder="Photo Shoot ID"),
        gr.Textbox(lines=1, placeholder="Main Image Key"),
        gr.Textbox(lines=1, placeholder="Compare Image Key")
    ], 
    outputs="text"
)

iface.launch()