import gradio as gr
import random
import time
import os
from glob import glob
from PIL import Image
import torchvision.transforms as transforms

image_prefix = "/deep/u/eprakash/AngioSeg/diffusion/cxr_synthetic_data_25_no_transform/synth/"
image_ids = glob(os.path.join(image_prefix, '*' + '.png'))
image_ids = list(set([os.path.splitext(os.path.basename(p))[0].split("_")[0] for p in image_ids]))
save_path = "cxr_ranks"

def load_img(img_path, size=1024):
    img = Image.open(img_path).convert('RGB')
    transform_list = [transforms.Resize((size, size))]
    transform = transforms.Compose(transform_list)
    img = transform(img)
    return img

def find_completed_idxs(save_path=save_path):
    files = os.listdir(save_path)
    if len(files) == 0:
        return [-1]
    else:
        file_list = []
        for f in files:
            f = int(f.split(".")[0])
            file_list.append(f)
        file_list = sorted(file_list)
        return file_list

def load_next(rank, img_1, mask_1, img_2, mask_2, img_3, mask_3, img_4, mask_4, example, ids=image_ids, image_prefix=image_prefix, save_path=save_path):
    if int(example) == len(image_ids) - 1:
        return [None, None, None, None, None, None, None]
    else:
        file_list = find_completed_idxs()
        if (int(example) not in file_list):
            r = str(image_ids[int(example)]) + "," + rank
            r_fp = open(save_path + "/" + str(int(example)) +".txt", "w")
            r_fp.write(r + "\n")
            r_fp.close()
        file_list = find_completed_idxs()
        example = file_list[-1] + 1
        rank = ""
        img_1 = gr.Image(label="Sample #1", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_0.png"), interactive=False)
        mask_1 = gr.Image(label="Mask", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_mask_1.png"), interactive=False)
        img_2 = gr.Image(label="Sample #2", value=load_img(image_prefix+ str(image_ids[int(example)]) + "_synthetic_1.png"), interactive=False)
        mask_2 = gr.Image(label="Mask", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_mask_2.png"), interactive=False)
        img_3 = gr.Image(label="Sample #3", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_2.png"), interactive=False)
        mask_3 = gr.Image(label="Mask", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_mask_3.png"), interactive=False)
        img_4 = gr.Image(label="Sample #4", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_3.png"), interactive=False)
        mask_4 = gr.Image(label="Mask", value=load_img(image_prefix + str(image_ids[int(example)]) + "_synthetic_mask_4.png"), interactive=False)
        return [rank, img_1, mask_1, img_2, mask_2, img_3, mask_3, img_4, mask_4, example]

with gr.Blocks() as demo:
    last_idx = -1
    example = gr.Number(label="Example #. Click next for #-1 (blank starting page).", value=last_idx, interactive=False)
    rank = gr.Textbox(label="Rankings (Best to worst, comma-separated, no spaces).")
    with gr.Column(scale=1):
        with gr.Row():
            mask_1 = gr.Image(label="Mask", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
            img_1 = gr.Image(label="Sample #1", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
        with gr.Row():
            mask_2 = gr.Image(label="Mask", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
            img_2 = gr.Image(label="Sample #2", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
        with gr.Row():
            mask_3 = gr.Image(label="Mask", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
            img_3 = gr.Image(label="Sample #3", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
        with gr.Row():
            mask_4 = gr.Image(label="Mask", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
            img_4 = gr.Image(label="Sample #4", value=load_img("/deep/u/eprakash/blank.jpg"), interactive=False)
    next_btn = gr.Button(value="Next")
    next_btn.click(fn=load_next, inputs=[rank, img_1, mask_1, img_2, mask_2, img_3, mask_3, img_4, mask_4, example], outputs=[rank, img_1, mask_1, img_2, mask_2, img_3, mask_3, img_4, mask_4, example], queue=False)
    demo.queue()
    demo.launch(share=True)