import os
os.system('pip install paddlepaddle')
os.system('pip install paddleocr')
from paddleocr import PaddleOCR, draw_ocr
from PIL import Image
import gradio as gr
import torch

torch.hub.download_url_to_file('https://i.imgur.com/aqMBT0i.jpg', 'example.jpg')

DISPLAY_WIDTH = 40
CYCLES = [20, 60, 100, 140, 180, 220]
PIXEL = '█' # Better than '#' for printing
EMPTY = ' ' # Better than '.' for printing



def solve(data, part_2 = False):
    cycle = 0
    sprite = 1 # middle position, we have pixels at 0 and 2
    total = 0
    X = 1
    crt = []
    for line in data.split("\n"):
        if cycle in [sprite-1, sprite, sprite+1]:
            crt.append(PIXEL)
        else:
            crt.append(EMPTY)
        cycle += 1
        if cycle in CYCLES:
            total += X * cycle
        if line.startswith("addx"):
            if cycle in [sprite-1, sprite, sprite+1]:
                crt.append(PIXEL)
            else:
                crt.append(EMPTY)
            cycle += 1
            if cycle in CYCLES:
                total += X * cycle
            X += int(line.split()[-1])
            sprite = X
        if part_2:
            # Go back to first position after 40 pixels
            cycle = cycle % DISPLAY_WIDTH

    print("Solution to part 1: ", total)
    res = "\n".join(["".join(crt[i:i+DISPLAY_WIDTH]) for i in range(0, len(crt), DISPLAY_WIDTH)])
    print("Solution to part 2:")
    print(res)


    # Bonus: make an image and then use OCR
    # to extract the text.
    from PIL import Image
    import numpy as np
    import matplotlib.pylab as plt
    img = np.array(crt)

    plt.imshow(img, cmap="binary")
    plt.axis('off')
    plt.savefig("day_10.png")

    print(ocr.ocr("day_10.png"))
    img_path = "day_10.png"
    ocr = PaddleOCR(use_angle_cls=True, use_gpu=False)
    result = ocr.ocr(img_path, cls=True)[0]
    image = Image.open(img_path).convert('RGB')
    boxes = [line[0] for line in result]
    txts = [line[1][0] for line in result]
    scores = [line[1][1] for line in result]
    im_show = draw_ocr(image, boxes, txts, scores,
                       font_path='simfang.ttf')
    im_show = Image.fromarray(im_show)
    im_show.save('result.jpg')
    return 'result.jpg' 

title = 'PaddleOCR'
description = 'Gradio demo for PaddleOCR. PaddleOCR demo supports Chinese, English, French, German, Korean and Japanese.To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to load them. Read more at the links below.'
article = "<p style='text-align: center'><a href='https://www.paddlepaddle.org.cn/hub/scene/ocr'>Awesome multilingual OCR toolkits based on PaddlePaddle （practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices）</a> | <a href='https://github.com/PaddlePaddle/PaddleOCR'>Github Repo</a></p>"
examples = [['example.jpg','en']]
css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
gr.Interface(
    solve,
    [gr.File(file_types='text', label='Input'),
    gr.outputs.Image(type='file', label='Output')],
    title=title,
    description=description,
    article=article,
    examples=examples,
    css=css,
    enable_queue=True
    ).launch(debug=True)