# Portrait Photo Generator App

# Imports
from PIL import Image, ImageFilter
import numpy as np
from transformers import pipeline
import gradio as gr
import os

model = pipeline("image-segmentation", model="facebook/detr-resnet-50-panoptic")

pred = []

def img_resize(image):
    width = 1280
    width_percent = (width / float(image.size[0]))
    height = int((float(image.size[1]) * float(width_percent)))
    return image.resize((width, height))

def image_objects(image):
    global pred
    
    image = img_resize(image)
    pred = model(image)
    pred_object_list = [str(i)+'_'+x['label'] for i, x in enumerate(pred)]
    return gr.Dropdown.update(choices = pred_object_list, interactive = True)



def blurr_object(image, object, blur_strength):
    image = img_resize(image)

    object_number = int(object.split('_')[0])
    mask_array = np.asarray(pred[object_number]['mask'])/255
    image_array = np.asarray(image)

    mask_array_three_channel = np.zeros_like(image_array)
    mask_array_three_channel[:,:,0] = mask_array
    mask_array_three_channel[:,:,1] = mask_array
    mask_array_three_channel[:,:,2] = mask_array

    segmented_image = image_array*mask_array_three_channel

    blur_image = np.asarray(image.filter(ImageFilter.GaussianBlur(radius=blur_strength)))
    mask_array_three_channel_invert = 1-mask_array_three_channel
    blur_image_reverse_mask = blur_image*mask_array_three_channel_invert
    
    #seg_out=image_array.astype(np.uint8)

    
    blurred_output_image = Image.fromarray((blur_image_reverse_mask).astype(np.uint8)+segmented_image.astype(np.uint8))
    for _ in range(int(blur_strength//2.5)):
        blurred_output_image = blurred_output_image.filter(ImageFilter.SMOOTH_MORE)
    return blurred_output_image

    
def get_seg(image, object):
    image = img_resize(image)

    #blur_image_reverse_mask = blur_image*mask_array_three_channel_invert
    seg_box=[]
    for i in range(len(pred)):
        object_number = int(object.split('_')[0])
        mask_array = np.asarray(pred[i]['mask'])/255
        image_array = np.asarray(image)
    
        mask_array_three_channel = np.zeros_like(image_array)
        mask_array_three_channel[:,:,0] = mask_array
        mask_array_three_channel[:,:,1] = mask_array
        mask_array_three_channel[:,:,2] = mask_array
    
        segmented_image = image_array*mask_array_three_channel
        seg_out=segmented_image.astype(np.uint8)
        seg_box.append(seg_out)  

    return(seg_box)



app = gr.Blocks()


with app:
    gr.Markdown(
            """
            ## Portrait Photo Generator
            - Create stunning portrait photos by blurring the background of your selected object.
            - Adjust the blurring strength using the slider.
            """)
    with gr.Row():
        with gr.Column():
            gr.Markdown(
            """
            ### Input Image
            """)
            image_input = gr.Image(type="pil")
            

        with gr.Column():
            with gr.Row():
                gr.Markdown(
                """
                ### Found Objects
                """)
            with gr.Row():
                blur_slider = gr.Slider(minimum=0.5, maximum=10, value=3, label="Adject Blur Strength")
            with gr.Row():
                object_output = gr.Dropdown(label="Select Object From Dropdown")

    
    with gr.Row():
        with gr.Column():
            gr.Markdown(
                """
                ### Blurred Image Output
                """)
            image_output = gr.Image()
        with gr.Column():
            seg_btn = gr.Button(label="Run")
            gal1=gr.Gallery(type="filepath").style(grid=10)

    seg_btn.click(get_seg, inputs=[image_input,object_output], outputs=gal1)

    
    image_input.change(fn=image_objects, 
        inputs=image_input, 
        outputs=object_output
        )

    object_output.change(fn=blurr_object, 
        inputs=[image_input, object_output, blur_slider],
        outputs=[image_output])

    blur_slider.change(fn=blurr_object, 
        inputs=[image_input, object_output, blur_slider],
        outputs=[image_output])
    

app.launch()