src/picture_box_model.py

import io
import numpy as np

from PIL import Image as PIL_Image # gltflibのImageと被るので別名にする。
import struct
import uuid

from gltflib import (
    GLTF, GLTFModel, Asset, Scene, Node, Mesh, Primitive, Attributes, Buffer, BufferView, Image, Texture, TextureInfo, Material, Sampler, Accessor, AccessorType,
    BufferTarget, ComponentType, GLBResource, PBRMetallicRoughness)

# 共通バイナリ情報
# 頂点データ(POSITION)
vertices = [
    [ 1.0,  1.0, -1.0,],
    [ 1.0,  1.0, -1.0,],
    [ 1.0,  1.0, -1.0,],
    [ 1.0, -1.0, -1.0,],
    [ 1.0, -1.0, -1.0,],
    [ 1.0, -1.0, -1.0,],
    [ 1.0,  1.0,  1.0,],
    [ 1.0,  1.0,  1.0,],
    [ 1.0,  1.0,  1.0,],
    [ 1.0, -1.0,  1.0,],
    [ 1.0, -1.0,  1.0,],
    [ 1.0, -1.0,  1.0,],
    [-1.0,  1.0, -1.0,],
    [-1.0,  1.0, -1.0,],
    [-1.0,  1.0, -1.0,],
    [-1.0, -1.0, -1.0,],
    [-1.0, -1.0, -1.0,],
    [-1.0, -1.0, -1.0,],
    [-1.0,  1.0,  1.0,],
    [-1.0,  1.0,  1.0,],
    [-1.0,  1.0,  1.0,],
    [-1.0, -1.0,  1.0,],
    [-1.0, -1.0,  1.0,],
    [-1.0, -1.0,  1.0,],
]
vertex_bytearray = bytearray()
for vertex in vertices:
    for value in vertex:
        vertex_bytearray.extend(struct.pack('f', value))
vertex_bytelen = len(vertex_bytearray)
mins = [min([vertex[i] for vertex in vertices]) for i in range(3)]
maxs = [max([vertex[i] for vertex in vertices]) for i in range(3)]

# 法線データ(NORMAL)
normals = [
    [ 0.0,  0.0, -1.0,],
    [ 0.0,  1.0, -0.0,],
    [ 1.0,  0.0, -0.0,],
    [ 0.0, -1.0, -0.0,],
    [ 0.0,  0.0, -1.0,],
    [ 1.0,  0.0, -0.0,],
    [ 0.0,  0.0,  1.0,],
    [ 0.0,  1.0, -0.0,],
    [ 1.0,  0.0, -0.0,],
    [ 0.0, -1.0, -0.0,],
    [ 0.0,  0.0,  1.0,],
    [ 1.0,  0.0, -0.0,],
    [-1.0,  0.0, -0.0,],
    [ 0.0,  0.0, -1.0,],
    [ 0.0,  1.0, -0.0,],
    [-1.0,  0.0, -0.0,],
    [ 0.0, -1.0, -0.0,],
    [ 0.0,  0.0, -1.0,],
    [-1.0,  0.0, -0.0,],
    [ 0.0,  0.0,  1.0,],
    [ 0.0,  1.0, -0.0,],
    [-1.0,  0.0, -0.0,],
    [ 0.0, -1.0, -0.0,],
    [ 0.0,  0.0,  1.0,],
]
normal_bytearray = bytearray()
for normal in normals:
    for value in normal:
        normal_bytearray.extend(struct.pack('f', value))
normal_bytelen = len(normal_bytearray)

# テクスチャ座標(TEXCOORD_0)
texcoord_0s = [
    [0.9, 0.1],[0.9, 0.0],[1.0, 0.1],
    [0.9, 1.0],[0.9, 0.9],[1.0, 0.9],
    [0.9, 0.1],[0.9, 0.1],[0.9, 0.1],
    [0.9, 0.9],[0.9, 0.9],[0.9, 0.9],
    [0.0, 0.1],[0.1, 0.1],[0.1, 0.0],
    [0.0, 0.9],[0.1, 1.0],[0.1, 0.9],
    [0.1, 0.1],[0.1, 0.1],[0.1, 0.1],
    [0.1, 0.9],[0.1, 0.9],[0.1, 0.9],
]
texcoord_0_bytearray = bytearray()
for texcoord_0 in texcoord_0s:
    for value in texcoord_0:
        texcoord_0_bytearray.extend(struct.pack('f', value))
texcoord_0_bytelen = len(texcoord_0_bytearray)

# 頂点インデックス
vertex_indices = [
     1, 14, 20,
     1, 20,  7,
    10,  6, 19,
    10, 19, 23,
    21, 18, 12,
    21, 12, 15,
    16,  3,  9,
    16,  9, 22,
     5,  2,  8,
     5,  8, 11,
    17, 13,  0,
    17,  0,  4
]

vertex_index_bytearray = bytearray()
for value in vertex_indices:
    vertex_index_bytearray.extend(struct.pack('H', value))
vertex_index_bytelen = len(vertex_index_bytearray)

def create_picture_box_model(img_bytearray):

    # 画像の取得
    img = PIL_Image.open(img_bytearray).convert('RGB')

    # 辺の長さが8で割れる数値になるように調整
    img = img.resize((8 * (img.size[0] // 8), 8 * (img.size[1] // 8)))
    temp_img = PIL_Image.new('RGB', (int(img.size[0] * 1.25), int(img.size[1] * 1.25)), 'white')
    temp_img.paste(img, (int(temp_img.size[0] / 10), int(temp_img.size[1] / 10)))
    img = temp_img.copy()

    for offset_x in range(0, int(temp_img.size[0] / 10)):
        img.paste(img.crop((int(temp_img.size[0] / 10)+1, 0, int(temp_img.size[0] / 10)+2, img.size[1])), (offset_x, 0))  
    for offset_x in range(int(temp_img.size[0] / 10 * 9), img.size[0]):
        img.paste(img.crop((int(temp_img.size[0] / 10 * 9) - 2, 0, int(temp_img.size[0] / 10 *9) - 1, img.size[1])), (offset_x, 0))  

    for offset_y in range(0, int(temp_img.size[1] / 10)):
        img.paste(img.crop((0, int(temp_img.size[1] / 10) + 1, img.size[0], int(temp_img.size[1] / 10) + 2)), (0, offset_y))  
    for offset_y in range(int(temp_img.size[1] / 10 * 9), img.size[1]):
        img.paste(img.crop((0, int(temp_img.size[1] / 10 * 9) - 2, img.size[0], int(temp_img.size[1] / 10 * 9) - 1)), (0, offset_y))  

    img_bytearray = io.BytesIO()
    img.save(img_bytearray, format="JPEG", quality=95)
    img_bytearray = img_bytearray.getvalue()
    img_bytelen = len(img_bytearray)

    # 3Dモデルのスケールの計算
    scale_factor = np.power(img.size[0] * img.size[1], 0.5)
    scale = (img.size[0] / scale_factor, img.size[1] / scale_factor, 0.1)

    # バイナリデータ部分の結合
    bytearray_list = [
        vertex_bytearray,
        normal_bytearray,
        texcoord_0_bytearray,
        vertex_index_bytearray,
        img_bytearray,
    ]
    bytelen_list = [
        vertex_bytelen,
        normal_bytelen,
        texcoord_0_bytelen,
        vertex_index_bytelen,
        img_bytelen,
    ]
    bytelen_cumsum_list = list(np.cumsum(bytelen_list))
    bytelen_cumsum_list = list(map(lambda x: int(x), bytelen_cumsum_list))

    all_bytearray = bytearray()
    for temp_bytearray in bytearray_list:
        all_bytearray.extend(temp_bytearray)
    offset_list = [0] + bytelen_cumsum_list # 最初のオフセットは0
    offset_list.pop() # 末尾を削除

    # リソースの作成
    resources = [GLBResource(data=all_bytearray)]

    # 各種設定
    # アセット
    asset=Asset()

    # バッファ
    buffers = [Buffer(byteLength=len(all_bytearray))]

    # バッファビュー
    bufferViews = [
        BufferView(buffer=0, byteOffset=offset_list[0], byteLength=bytelen_list[0], target=BufferTarget.ARRAY_BUFFER.value),
        BufferView(buffer=0, byteOffset=offset_list[1], byteLength=bytelen_list[1], target=BufferTarget.ARRAY_BUFFER.value),
        BufferView(buffer=0, byteOffset=offset_list[2], byteLength=bytelen_list[2], target=BufferTarget.ARRAY_BUFFER.value),
        BufferView(buffer=0, byteOffset=offset_list[3], byteLength=bytelen_list[3], target=BufferTarget.ELEMENT_ARRAY_BUFFER.value),
        BufferView(buffer=0, byteOffset=offset_list[4], byteLength=bytelen_list[4], target=None),
    ]

    # アクセサー
    accessors = [
        Accessor(bufferView=0, componentType=ComponentType.FLOAT.value, count=len(vertices), type=AccessorType.VEC3.value, max=maxs, min=mins),
        Accessor(bufferView=1, componentType=ComponentType.FLOAT.value, count=len(normals), type=AccessorType.VEC3.value, max=None, min=None),
        Accessor(bufferView=2, componentType=ComponentType.FLOAT.value, count=len(texcoord_0s), type=AccessorType.VEC2.value, max=None, min=None),
        Accessor(bufferView=3, componentType=ComponentType.UNSIGNED_SHORT.value, count=len(vertex_indices), type=AccessorType.SCALAR.value, max=None, min=None)
    ]

    # イメージ
    images=[
        Image(mimeType='image/jpeg', bufferView=4),
    ]

    # サンプラー
    samplers = [Sampler(magFilter=9728, minFilter=9984)] # magFilter:最近傍フィルタリング、minFilter:ミップマップ+最近傍フィルタリング

    # テクスチャ
    textures = [
        Texture(name='Image',sampler=0,source=0),
    ]

    # マテリアル
    materials = [
        Material(
            pbrMetallicRoughness=PBRMetallicRoughness(
                baseColorTexture=TextureInfo(index=0),
                metallicFactor=0,
                roughnessFactor=0.5
            ),
            name='Material0',
            alphaMode='BLEND',
            doubleSided=False
        ),
    ]

    # メッシュ
    meshes = [
        Mesh(name='Image', primitives=[Primitive(attributes=Attributes(POSITION=0, NORMAL=1,TEXCOORD_0=2),indices=3, material=0)]),
    ]

    # ノード
    nodes = [
        Node(mesh=0,rotation=None, scale=scale),
    ]

    # シーン
    scene = 0
    scenes = [Scene(name='Scene', nodes=[0])]

    model = GLTFModel(
        asset=asset,
        buffers=buffers,
        bufferViews=bufferViews,
        accessors=accessors,
        images=images,
        samplers=samplers,
        textures=textures,
        materials=materials,
        meshes=meshes,
        nodes=nodes,
        scene=scene,
        scenes=scenes
    )

    gltf = GLTF(model=model, resources=resources)

    tmp_filename = uuid.uuid4().hex
    model_path = f'../tmp/{tmp_filename}.glb'

    gltf.export(model_path)

    return model_path