#######################################################################################
#
# MIT License
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# Copyright (c) [2025] [leonelhs@gmail.com]
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#
#
# This file implements an API endpoint GFPGAN system.
# It provides functionality to enhances an image by upscaling it 4 times its original size .
#
#
# Source code is based on or inspired by several projects.
# For more details and proper attribution, please refer to the following resources:
#
# - [GFPGAN] - [https://github.com/TencentARC/GFPGAN]

import gradio as gr
import numpy as np
from facexlib.utils.face_restoration_helper import FaceRestoreHelper

from tiny_esrgan import TinyESRGAN
from tiny_gfpgan import TinyGFPGAN

face_enhancer = TinyGFPGAN()
background_enhancer = TinyESRGAN()
face_helper = FaceRestoreHelper(upscale_factor=4, use_parse=True, model_rootpath='gfpgan/weights')

def predict(img):

    img = np.asarray(img)
    face_helper.clean_all()
    face_helper.read_image(img)
    # get face landmarks for each face
    face_helper.get_face_landmarks_5(eye_dist_threshold=5)
    face_helper.align_warp_face()

    face_helper.restored_faces = face_enhancer.enhance(face_helper.cropped_faces)
    bg = background_enhancer.enhance(img)

    face_helper.get_inverse_affine(None)
    return face_helper.paste_faces_to_input_image(upsample_img=bg)



app = gr.Interface(
    predict, [
        gr.Image(type="pil", label="Image input"),
    ], [
        gr.Image(type="numpy", label="Image face enhanced")
    ],
    title="Image enhancer",
    description="GFPGAN")

app.launch(share=False, debug=True, show_error=True, mcp_server=True)
app.queue()