generate_minis_functions.py

# -*- coding: utf-8 -*-
"""
Created on Tue Jul 24 10:12:16 2018

@author: Matthias N.
"""
import numpy as np
import cv2 as cv
from PIL import Image
import json
from urllib.request import Request, urlopen
from fake_useragent import UserAgent
from greedypacker import greedypacker

## settings
do_these = ['Marid', 'Sea Spawn', 'Sea Spawn', 'Sea Spawn', 'Sea Spawn', 'Sea Spawn', 'Sea Spawn', 'Sea Spawn', 'Leviathan', 'Water Elemental', 'Water Elemental', 'Water Elemental', 'Storm Giant', 'Sea Hag', 'Sea Hag']
paper_format = 'a4'
print_margin = np.array([3.5,4]) #left&right, top&bottom in mm per side
dpmm = 10 # resolution


## init
font = cv.FONT_HERSHEY_SIMPLEX
paper = {'a3': np.array([297,420]), 'a4': np.array([210,297])}
canvas = (paper[paper_format] - 2*print_margin) * dpmm
ua = UserAgent()
header = {'User-Agent':str(ua.chrome)}
with open('monsters.json', encoding='utf-8') as data_file:
    monsters = json.loads(data_file.read())
    

## main function    
def create_mini(monster):
    # load values
    try:
        creature_size = monsters[monster]['size']
        img_url = monsters[monster]['img_url']
    except:
        return 'Monster not found.'
    
    if img_url == '':
        return 'No image url found.'
    
    # more settings
    base_width = 24
    if creature_size in ['Medium','Small','Tiny']:
        m_width = base_width
        max_height = 40
        n_height = 8
        font_size = 1.15
        font_width = 1
    elif creature_size == 'Large':
        m_width = base_width * 2
        max_height = 50
        n_height = 10
        font_size = 2
        font_width = 2
    elif creature_size == 'Huge':
        m_width = base_width * 3
        max_height = 60
        n_height = 12
        font_size = 2.5
        font_width = 2
    elif creature_size == 'Gargantuan':
        m_width = base_width * 4
        max_height = 80
        n_height = 14
        font_size = 3
        font_width = 3
    else:
        return 'Creature size invalid.'
    
    min_height = 40
    b_height = m_width
    width = m_width*dpmm


    ## generate name plate
    text = monster
    n_img = np.zeros((n_height*dpmm,width,3), np.uint8)+255
    
    x_margin = 0
    y_margin = 0

    # find optimal font size
    while x_margin < 2 or y_margin < 10:
        font_size = round(font_size - 0.05,2)
        textsize = cv.getTextSize(text, font, font_size, font_width)[0]
        x_margin = n_img.shape[1] - textsize[0]
        y_margin = n_img.shape[0] - textsize[1]
    
    # write text        
    textX = np.floor_divide(x_margin,2)
    textY = np.floor_divide(n_img.shape[0] + textsize[1],2)
    cv.putText(n_img, text, (textX, textY), font, font_size, (0, 0, 0), font_width, cv.LINE_AA)
    cv.rectangle(n_img, (0,0), (n_img.shape[1]-1,n_img.shape[0]-1), (0,0,0), thickness=1)
    
    ## generate mimiature image
    req = Request(img_url, headers=header)
          
    with urlopen(req) as resp:
        arr = np.asarray(bytearray(resp.read()), dtype=np.uint8)
        m_img = cv.imdecode(arr, -1) # Load it 'as it is'
    
    # replace alpha channel with white (for .png, etc)
    if m_img.shape[2] == 4:
        alpha_channel = m_img[:,:,3]
        mask = (alpha_channel == 0)
        mask = np.dstack((mask,mask,mask))
        color = m_img[:,:,:3]
        color[mask] = 255
        m_img = color

    # resize the image and/or add padding
    if m_img.shape[1] > width-2:
        f = (width-2) / m_img.shape[1]
        m_img = cv.resize(m_img, (0,0), fx=f, fy=f)
        white_vert = np.zeros((m_img.shape[0],1,3), np.uint8)+255
        m_img = np.concatenate((white_vert,m_img,white_vert),axis=1)
        
    if m_img.shape[0] > max_height*dpmm-2:
        f = (max_height*dpmm-2) / m_img.shape[0]
        m_img = cv.resize(m_img, (0,0), fx=f, fy=f)
        white_horiz = np.zeros((1,m_img.shape[1],3), np.uint8)+255
        m_img = np.concatenate((white_horiz,m_img,white_horiz),axis=0)
        
    if m_img.shape[0] < min_height*dpmm:
        diff = min_height*dpmm-m_img.shape[0]
        top = np.floor_divide(diff,2)
        bottom = top
        if diff%2 == 1: bottom += 1
        m_img = np.concatenate((np.zeros((top,m_img.shape[1],3), np.uint8)+255,m_img,np.zeros((top,m_img.shape[1],3), np.uint8)+255),axis=0)
    
    if m_img.shape[1] < width:
        diff = width-m_img.shape[1]
        left = np.floor_divide(diff,2)
        right = left
        if diff%2 == 1: right += 1
        m_img = np.concatenate((np.zeros((m_img.shape[0],left,3), np.uint8)+255,m_img,np.zeros((m_img.shape[0],right,3), np.uint8)+255),axis=1)
        
    cv.rectangle(m_img, (0,0), (m_img.shape[1]-1,m_img.shape[0]-1), (0,0,0), thickness=1)
    
    ## create mini base
    demi_base = b_height//2*dpmm
    if creature_size == 'Gargantuan': feet_mod = 1
    else: feet_mod = 2
    base_height = int(np.floor(demi_base*feet_mod))
    b_img = np.zeros((base_height,width,3), np.uint8)+255
    cv.rectangle(b_img, (0,0), (b_img.shape[1]-1,demi_base-1), (0,0,0), thickness=-1)
    cv.rectangle(b_img, (0,0), (b_img.shape[1]-1,b_img.shape[0]-1), (0,0,0), thickness=1)
    
    ## construct full miniature
    img = np.concatenate((m_img,n_img,b_img),axis=0)
    flipped_img = cv.flip(img, -1)
    img = np.append(flipped_img,img,axis=0)
    # convert to PIL image so we can save it with the correct dpi
    RGB_img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
    im_pil = Image.fromarray(RGB_img)
    im_pil.save("minis/"+monster+".png", dpi=(25.4*dpmm,25.4*dpmm))
    
    return img

## generate all mini images
minis = []
for m in do_these:
    print('Doing {}...'.format(m))
    mini = create_mini(m)
    if not isinstance(mini, str):
        minis.append(mini)
    else:
        print('{} skipped with error: {}'.format(m,mini))

## optimization algorithm to align images on canvas
M = greedypacker.BinManager(canvas[0], canvas[1], pack_algo='shelf', heuristic='best_width_fit', wastemap=True, rotation=True)
its = {}
item_id = 0
for it in minis:
    its[item_id] = it
    item = greedypacker.Item(it.shape[1],it.shape[0],item_id)
    M.add_items(item)
    item_id += 1

M.execute()
result = M.bins


## Create sheets
sheet_nr = 1
for r in result:
    img = np.zeros((canvas[1],canvas[0],3), np.uint8)+255
    for it in r.minis:
        x = int(it.x)
        y = int(it.y)
        w = int(it.width)
        h = int(it.height)
        it_id = int(it.item_id)
        m_img = its[it_id]
        test = m_img
        if w > h: # rotated (only works as long as minis always have height > width, keep in mind if editing)
            m_img = np.rot90(m_img, axes=(1,0))
        shape = m_img.shape
        img[y:y+shape[0],x:x+shape[1],:] = m_img
    
    # save sheets
    RGB_img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
    im_pil = Image.fromarray(RGB_img)
    im_pil.save("sheets/sheet_"+str(sheet_nr)+".png", dpi=(25.4*dpmm,25.4*dpmm))
    sheet_nr += 1

    # display result if you want
    #img_small =  cv.resize(img, (0,0), fx=.6, fy=.6)
    #cv.imshow('Img',img_small)
    #cv.waitKey(0)