translate Japanese comments to English

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from PIL import Image as PIL_Image # gltflibのImageと被るので別名にする。
+from PIL import Image as PIL_Image # Renaming to avoid conflict with Image from gltflib
 from io import BytesIO
 import json
 import os
@@ -24,7 +24,7 @@ def create_3dmodel(model_no, title, color, mark, historic_site_type, difficulty,
 
     img_bytearray = BytesIO()
     image['background'].save(img_bytearray, "JPEG", quality=95)
-    img_bytearray.seek(0) # 画像の先頭にシークしないと空データになってしまう。
+    img_bytearray.seek(0) # Seek to the beginning of the image, otherwise it results in empty data.
 
     option_dict = {
         'タイトル': title,
@@ -36,32 +36,31 @@ def create_3dmodel(model_no, title, color, mark, historic_site_type, difficulty,
         '厚み': '有' if is_thick else '無',
     }
 
-    # model_noのコード値決定ルールを接頭語を付けた場合分けやファクトリ―クラスの作成を検討した方が良い
+    # Consider implementing model_no categorization rules or creating a factory class
     if model_no not in ['A', 'B']:
-        # カード画像(表面)の作成
+        # Create the card image (front side)
         if model_no == '1':
             front_img_bytearray = create_historic_site_card_image(img_bytearray, option_dict)
         else:
             front_img_bytearray = create_card_image(model_no, img_bytearray, option_dict)
 
-        # カード画像(裏面)の取得
+        # Retrieve the card image (back side)
         back_path = constants.back_card_img_dict[model_no]
         back_img = PIL_Image.open(back_path)
         back_img_bytearray = BytesIO()
         back_img.convert('RGB').save(back_img_bytearray, "JPEG", quality=95)
-        back_img_bytearray.seek(0) # 画像の先頭にシークしないと空データになってしまう。
+        back_img_bytearray.seek(0) # Seek to the beginning of the image, otherwise it results in empty data
 
-        # カードの3Dモデルの作成(戻り値は作成したモデルのパス)
+        # Create a 3D model of the card (return value is the path of the created model)
         model_path = create_card_model(front_img_bytearray, back_img_bytearray, option_dict)
         
     else:
-        # 3Dモデルの作成(戻り値は作成したモデルのパス)
+        # Create a 3D model of the card (return value is the path of the created model)
         if model_no == 'A':
             model_path = create_picture_box_model(img_bytearray)
         if model_no == 'B':
             model_path = create_extracted_objects_model(img_bytearray)
     
-    # 作成した3Dモデルの送信
     return model_path
 
 with gr.Blocks() as demo:

src/card_model.py

@@ -1,6 +1,6 @@
 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。
+from PIL import Image as PIL_Image # Renaming to avoid conflict with Image from gltflib
 import struct
 import uuid
 
@@ -8,12 +8,13 @@ from gltflib import (
     GLTF, GLTFModel, Asset, Scene, Node, Mesh, Primitive, Attributes, Buffer, BufferView, Image, Texture, TextureInfo, Material, Sampler, Accessor, AccessorType,
     BufferTarget, ComponentType, GLBResource, PBRMetallicRoughness)
 
-# 共通設定情報
-# バイナリ部分のオフセットやサイズに関わらない部分は予め定義できる。
-# アセット
+# Common configuration information
+# Parts that are independent of the binary section's offset and size can be predefined.
+
+# Asset
 asset=Asset()
 
-# イメージ
+# Image
 images=[
     Image(mimeType='image/jpeg', bufferView=4),
     Image(mimeType='image/jpeg',bufferView=5),
@@ -22,20 +23,20 @@ images=[
     Image(mimeType='image/jpeg',bufferView=8),
     Image(mimeType='image/jpeg',bufferView=9),
 ]
-# 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
+# Sampler
+samplers = [Sampler(magFilter=9728, minFilter=9984)] # magFilter: Nearest filtering, minFilter: Mipmap + Nearest filtering
 
-# テクスチャ
+# Texture
 textures = [
     Texture(name='Front',sampler=0,source=0),
     Texture(name='Back',sampler=0,source=1),
-    Texture(name='Left',sampler=0,source=2), # 左
-    Texture(name='Right',sampler=0,source=3), # 右
-    Texture(name='Top',sampler=0,source=4), # 上
-    Texture(name='Bottom',sampler=0,source=5), # 下
+    Texture(name='Left',sampler=0,source=2),
+    Texture(name='Right',sampler=0,source=3),
+    Texture(name='Top',sampler=0,source=4),
+    Texture(name='Bottom',sampler=0,source=5),
 ]
 
-# マテリアル
+# Material
 materials = [
     Material(
         pbrMetallicRoughness=PBRMetallicRoughness(
@@ -99,7 +100,7 @@ materials = [
     ),
 ]
 
-# メッシュ
+# Mesh
 meshes = [
     Mesh(name='Front', primitives=[Primitive(attributes=Attributes(POSITION=0, NORMAL=1,TEXCOORD_0=2), indices=3, material=0)]),
     Mesh(name='Back', primitives=[Primitive(attributes=Attributes(POSITION=0, NORMAL=1,TEXCOORD_0=2), indices=3, material=1)]),
@@ -113,44 +114,44 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
 
     is_thick = True if option_dict['厚み'] == '有' else False
 
-    # 表面画像
+    # Front image
     front_img = PIL_Image.open(front_img_bytearray).convert('RGB')
     front_bytearray = io.BytesIO()
-    front_img.save(front_bytearray, format="JPEG", quality=95) # JPEG保存を強制
+    front_img.save(front_bytearray, format="JPEG", quality=95) # Force JPEG format for saving
     front_bytearray = front_bytearray.getvalue()
     front_bytelen = len(front_bytearray)
 
-    # 裏面画像
+    # Back image
     back_img = PIL_Image.open(back_img_bytearray).convert('RGB')
     back_bytearray = io.BytesIO()
-    back_img.save(back_bytearray, format="JPEG", quality=95) # JPEG保存を強制
+    back_img.save(back_bytearray, format="JPEG", quality=95) # Force JPEG format for saving
     back_bytearray = back_bytearray.getvalue()
     back_bytelen = len(back_bytearray)
 
-    # 側面画像の作成(裏面の端の色を延長する)
+    # Create side image (extend the color of the edges of the back side)
     back_img_array = np.array(back_img)
     left_side_img = PIL_Image.fromarray(np.tile(back_img_array[:, [0], :], [1, 32, 1]))
     right_side_img = PIL_Image.fromarray(np.tile(back_img_array[:, [back_img_array.shape[1] - 1], :], [1, 32, 1]))
     top_side_img = PIL_Image.fromarray(np.tile(back_img_array[[0], :, :], [32, 1, 1]))
     bottom_side_img = PIL_Image.fromarray(np.tile(back_img_array[[back_img_array.shape[0] - 1], :, :], [32, 1, 1]))
     left_side_bytearray = io.BytesIO()
-    left_side_img.save(left_side_bytearray, format="JPEG", quality=95) # JPEG保存を強制
+    left_side_img.save(left_side_bytearray, format="JPEG", quality=95) # Force JPEG format for saving
     left_side_bytearray = left_side_bytearray.getvalue()
     left_side_bytelen = len(left_side_bytearray)
     right_side_bytearray = io.BytesIO()
-    right_side_img.save(right_side_bytearray, format="JPEG", quality=95) # JPEG保存を強制
+    right_side_img.save(right_side_bytearray, format="JPEG", quality=95) # Force JPEG format for saving
     right_side_bytearray = right_side_bytearray.getvalue()
     right_side_bytelen = len(right_side_bytearray)
     top_side_bytearray = io.BytesIO()
-    top_side_img.save(top_side_bytearray, format="JPEG", quality=95) # JPEG保存を強制
+    top_side_img.save(top_side_bytearray, format="JPEG", quality=95) # Force JPEG format for saving
     top_side_bytearray = top_side_bytearray.getvalue()
     top_side_bytelen = len(top_side_bytearray)
     bottom_side_bytearray = io.BytesIO()
-    bottom_side_img.save(bottom_side_bytearray, format="JPEG", quality=95) # JPEG保存を強制
+    bottom_side_img.save(bottom_side_bytearray, format="JPEG", quality=95) # Force JPEG format for saving
     bottom_side_bytearray = bottom_side_bytearray.getvalue()
     bottom_side_bytelen = len(bottom_side_bytearray)
 
-    # 頂点データ(POSITION)
+    # Vertex data(POSITION)
     vertices = [
         (-1.0, -1.0, 0.0),
         ( 1.0, -1.0, 0.0),
@@ -165,7 +166,7 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
     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)
+    # Normal data(NORMAL)
     normals = [( 0.0,  0.0, 1.0)] * 4
     normal_bytearray = bytearray()
     for normal in normals:
@@ -173,7 +174,7 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
             normal_bytearray.extend(struct.pack('f', value))
     normal_bytelen = len(normal_bytearray)
 
-    # テクスチャ座標(TEXCOORD_0)
+    # Texture coordinates(TEXCOORD_0)
     texcoord_0s = [
         (0.0, 1.0),
         (1.0, 1.0),
@@ -186,14 +187,14 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
             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
     vertex_indices = [0, 1, 2, 1, 3, 2]
     vertex_index_bytearray = bytearray()
     for value in vertex_indices:
         vertex_index_bytearray.extend(struct.pack('H', value))
     vertex_index_bytelen = len(vertex_index_bytearray)
 
-    # バイナリデータ部分の結合
+    # Concatenation of the binary data section
     bytearray_list = [
         vertex_bytearray,
         normal_bytearray,
@@ -224,17 +225,16 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
     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
+    offset_list = [0] + bytelen_cumsum_list # The first offset is 0
+    offset_list.pop() # Remove the end
 
-    # リソースの作成
+    # GLBResource
     resources = [GLBResource(data=all_bytearray)]
 
-    # 各種設定
-    # バッファ
+    # Buffer
     buffers = [Buffer(byteLength=len(all_bytearray))]
 
-    # バッファビュー
+    # BufferView
     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),
@@ -248,7 +248,7 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
         BufferView(buffer=0, byteOffset=offset_list[9], byteLength=bytelen_list[9], target=None),
     ]
 
-    # アクセサー
+    # Accessor
     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),
@@ -256,7 +256,7 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
         Accessor(bufferView=3, componentType=ComponentType.UNSIGNED_SHORT.value, count=len(vertex_indices), type=AccessorType.SCALAR.value, max=None, min=None),
     ]
 
-    # ノード
+    # Node
     card_thickness = 0.025
     card_ratio_x = 0.8679999709129333
     card_ratio_y = 1.2130000591278076
@@ -277,7 +277,7 @@ def create_card_model(front_img_bytearray, back_img_bytearray, option_dict):
             Node(mesh=1, scale=[card_ratio_x, card_ratio_y, card_ratio_z], rotation=[0, 1, 0, 0])
         ]
 
-    # シーン
+    # Scene
     scene = 0
     if is_thick:
         scenes = [Scene(name='Scene', nodes=[0, 1, 2, 3, 4, 5])]

src/extracted_objects_model.py

@@ -1,6 +1,6 @@
 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。
+from PIL import Image as PIL_Image # Renaming to avoid conflict with Image from gltflib
 import cv2
 import struct
 import triangle
@@ -10,17 +10,17 @@ from gltflib import (
     GLTF, GLTFModel, Asset, Scene, Node, Mesh, Primitive, Attributes, Buffer, BufferView, Image, Texture, TextureInfo, Material, Sampler, Accessor, AccessorType,
     BufferTarget, ComponentType, GLBResource, PBRMetallicRoughness)
 
-# 表面及び裏面の頂点リストの作成
+# Create vertex lists for both the front and back surfaces
 def make_front_and_back_vertex_list(coordinate_list, img):
 
-    # 表面の頂点
+    # Front surface vertices
     front_vertex_list = []
-    # 裏面の頂点
+    # Back surface vertices
     back_vertex_list = []
     for coordinates in coordinate_list:
         front_vertices = []
         back_vertices = []
-        # Y軸方向は画像とGLBで上下が逆になるので注意
+        # Note that the Y-axis direction is inverted between the image and GLB, so be careful
         for coordinate in coordinates:
             front_vertices.append((coordinate[0] * 2 / img.size[0] - 1.0, -(coordinate[1] * 2 / img.size[1] - 1.0), 0.2))
             back_vertices.append((coordinate[0] * 2 / img.size[0] - 1.0, -(coordinate[1] * 2 / img.size[1] - 1.0), -0.2))
@@ -30,13 +30,13 @@ def make_front_and_back_vertex_list(coordinate_list, img):
 
     return front_vertex_list, back_vertex_list
     
-# メッシュの各種情報の作成
+# Creation of various information for the mesh
 def make_mesh_data(coordinate_list, img):
     front_vertex_list, back_vertex_list = make_front_and_back_vertex_list(coordinate_list, img)
 
-    # 頂点データ(POSITION)
+    # Vertex data(POSITION)
     vertices = []
-    # 頂点インデックス決定時に使うオフセット値のリスト
+    # List of offset values used when determining vertex indices
     front_offset = 0
     front_offset_list = []
     back_offset_list = []
@@ -49,51 +49,51 @@ def make_mesh_data(coordinate_list, img):
         back_offset_list.append(back_offset)
         front_offset += len(front_vertices) + len(back_vertices)        
 
-    # 法線データ(NORMAL)
+    # Normal data(NORMAL)
     normals = []
     for front_vertices, back_vertices in zip(front_vertex_list, back_vertex_list):
         normals.extend([( 0.0,  0.0,  1.0)] * len(front_vertices))
         normals.extend([( 0.0,  0.0, -1.0)] * len(back_vertices))
 
-    # テクスチャ座標(TEXCOORD_0)
-    # 画像は左上原点になり、Y軸の上下を変える必要がある。
+    # Texture coordinates (TEXCOORD_0)
+    # The image origin is at the top-left, requiring an inversion of the Y-axis.
     texcoord_0s = [((vertex[0] + 1.0) / 2.0, 1.0 - ((vertex[1] + 1.0) / 2.0) ) for vertex in vertices]
 
-    # 頂点インデックス
+    # Vertex indices
     vertex_indices = []
     for front_vertices, back_vertices, front_offset, back_offset \
         in zip(front_vertex_list, back_vertex_list, front_offset_list, back_offset_list):
         polygon = {
             'vertices': np.array(front_vertices)[:, :2],
-            'segments': np.array([( i, (i + 1) % (len(front_vertices)) ) for i in range(len(front_vertices))])  # 各辺を定義
+            'segments': np.array([( i, (i + 1) % (len(front_vertices)) ) for i in range(len(front_vertices))]) # Define each edge
         }
         triangulate_result = triangle.triangulate(polygon, 'p')
-        vertex_indices.extend(list(np.array(triangulate_result['triangles']+front_offset).flatten())) # 表面
-        vertex_indices.extend(list((np.array(triangulate_result['triangles'])+back_offset).flatten())) # 裏面
+        vertex_indices.extend(list(np.array(triangulate_result['triangles']+front_offset).flatten())) # Front surface
+        vertex_indices.extend(list((np.array(triangulate_result['triangles'])+back_offset).flatten())) # Back surface
         vertex_indices.extend(list(np.array([[front_offset + i, 
                                               front_offset + (i + 1) % len(front_vertices), 
                                               back_offset + i] 
-                                               for i in range(len(front_vertices))]).flatten())) # 側面1
+                                               for i in range(len(front_vertices))]).flatten())) # Side surface 1
         vertex_indices.extend(list(np.array([[back_offset + i,
                                               back_offset + (i + 1) % len(back_vertices), 
-                                              front_offset+ (i + 1) % len(front_vertices)] for i in range(len(front_vertices))]).flatten())) # 側面2
+                                              front_offset+ (i + 1) % len(front_vertices)] for i in range(len(front_vertices))]).flatten())) # Side surface 2
             
     return vertices, normals, texcoord_0s, vertex_indices
 
 def create_extracted_objects_model(img_bytearray):
 
-    # 画像の取得
+    # Retrieve the image
     img = PIL_Image.open(img_bytearray).convert('RGB')
     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
+    # Calculate the scale of the 3D model
     scale_factor = np.power(img.size[0] * img.size[1], 0.5)
     scale = (img.size[0] / scale_factor, img.size[1] / scale_factor, 0.4)
 
-    # 画像主要部分の頂点の取得
+    # Retrieve vertices of the main part of the image
     base_color = img.getpixel((0, 0))
     mask = PIL_Image.new('RGB', img.size)
     for i in range(img.size[0]):
@@ -112,10 +112,10 @@ def create_extracted_objects_model(img_bytearray):
             coordinates.append((x, y))
         coordinate_list.append(coordinates)
     
-    # 各種データの作成
+    # Creation of associated data for the mesh
     vertices, normals, texcoord_0s, vertex_indices = make_mesh_data(coordinate_list, img)
     
-    # 頂点データ(POSITION)
+    # Vertex data(POSITION)
     vertex_bytearray = bytearray()
     for vertex in vertices:
         for value in vertex:
@@ -124,14 +124,14 @@ def create_extracted_objects_model(img_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)
+    # Normal data(NORMAL)
     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)
+    # Texture coordinates(TEXCOORD_0)
     texcoord_0s = [
     ((vertex[0] + 1.0) / 2.0, 1.0 - ((vertex[1] + 1.0) / 2.0) ) for vertex in vertices
     ]
@@ -141,13 +141,13 @@ def create_extracted_objects_model(img_bytearray):
             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
     vertex_index_bytearray = bytearray()
     for value in vertex_indices:
         vertex_index_bytearray.extend(struct.pack('H', value))
     vertex_index_bytelen = len(vertex_index_bytearray)
 
-    # バイナリデータ部分の結合
+    # Concatenation of the binary data section
     bytearray_list = [
         vertex_bytearray,
         normal_bytearray,
@@ -168,20 +168,19 @@ def create_extracted_objects_model(img_bytearray):
     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 = [0] + bytelen_cumsum_list # The first offset is 0
     offset_list.pop() # 末尾を削除
 
-    # リソースの作成
+    # GLBResource
     resources = [GLBResource(data=all_bytearray)]
 
-    # 各種設定
-    # アセット
+    # Asset
     asset=Asset()
 
-    # バッファ
+    # Buffer
     buffers = [Buffer(byteLength=len(all_bytearray))]
 
-    # バッファビュー
+    # BufferView
     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),
@@ -190,7 +189,7 @@ def create_extracted_objects_model(img_bytearray):
         BufferView(buffer=0, byteOffset=offset_list[4], byteLength=bytelen_list[4], target=None),
     ]
 
-    # アクセサー
+    # Accessor
     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),
@@ -198,20 +197,20 @@ def create_extracted_objects_model(img_bytearray):
         Accessor(bufferView=3, componentType=ComponentType.UNSIGNED_SHORT.value, count=len(vertex_indices), type=AccessorType.SCALAR.value, max=None, min=None)
     ]
 
-    # イメージ
+    # Image
     images=[
         Image(mimeType='image/jpeg', bufferView=4),
     ]
 
-    # サンプラー
+    # Sampler
     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
+    # Texture
     textures = [
         Texture(name='Main',sampler=0,source=0),
     ]
 
-    # マテリアル
+    # Material
     materials = [
         Material(
             pbrMetallicRoughness=PBRMetallicRoughness(
@@ -225,21 +224,22 @@ def create_extracted_objects_model(img_bytearray):
         ),
     ]
 
-    # メッシュ
+    # Mesh
     meshes = [
         Mesh(name='Main', primitives=[Primitive(attributes=Attributes(POSITION=0, NORMAL=1,TEXCOORD_0=2),
                                                 indices=3, material=0, mode=4)]),
     ]
 
-    # ノード
+    # Node
     nodes = [
         Node(mesh=0,rotation=None, scale=scale),
     ]
 
-    # シーン
+    # Scene
     scene = 0
     scenes = [Scene(name='Scene', nodes=[0])]
 
+    # GLTFModel
     model = GLTFModel(
         asset=asset,
         buffers=buffers,

src/front_card_image.py

@@ -3,27 +3,27 @@ from io import BytesIO
 
 from src.constants import front_card_img_dict
 
-# カード画像各領域のピクセル位置情報
-# 写真
+# Pixel position information for each area of the card image
+# Picture
 PICTURE_LT_XY = (65, 188)
 PICTURE_RB_XY = (802, 925)
 PICTURE_SIZE = (PICTURE_RB_XY[0] - PICTURE_LT_XY[0], PICTURE_RB_XY[1] - PICTURE_LT_XY[1])
 
-# タイトル
-# ある程度の余白を作る。
+# Title
+# Create some margin
 TITLE_LT_XY = (65, 45) 
-TITLE_RB_XY = (647, 132) # マーク挿入部分と重ならないような位置
+TITLE_RB_XY = (647, 132)
 TITLE_SIZE = (TITLE_RB_XY[0] - TITLE_LT_XY[0], TITLE_RB_XY[1] - TITLE_LT_XY[1])
 
-# 説明文本体
+# Main Body of Description
 DESCRIPTION_LT_XY = (46, 972)
 DESCRIPTION_RB_XY = (810, 1174)
 DESCRIPTION_SIZE = (DESCRIPTION_RB_XY[0] - DESCRIPTION_LT_XY[0], DESCRIPTION_RB_XY[1] - DESCRIPTION_LT_XY[1])
 
-# フォント関連
-# 明朝体
+# Font information
+# Ming Typeface
 font_selif_path = 'data/fonts/SourceHanSerif-Bold.otf'
-# ゴシック体
+# Gothic Typeface
 font_sanselif_path = 'data/fonts/SourceHanSans-Bold.otf'
 
 def crop_center(pil_img, crop_width, crop_height):
@@ -38,22 +38,22 @@ def crop_max_square(pil_img):
     
 def create_card_image(model_no, img_bytearray, option_dict):
 
-    # 画像の読み込みとトリミング
+    # Loading and Cropping of Picture
     picture_img = Image.open(img_bytearray)
     picture_img = crop_max_square(picture_img)
     picture_img = picture_img.resize(PICTURE_SIZE)
 
-    # カードの読み込み
+    # Loading of Card Frame
     card_img = Image.open(front_card_img_dict[model_no])
 
-    # 写真の埋め込み
+    # Embedding a Picture in the Card
     card_img.paste(picture_img, PICTURE_LT_XY)
 
-    # 各種書き込み準備
+    ## Preparing for editting the card image
     card_imgdraw = ImageDraw.Draw(card_img)
 
-    # タイトル埋め込み
-    # (複数行対応は必要ならば対応)
+    # Embedding the Title
+    # (Support for multiple lines if needed)
     title_font_size = 100
     while True:
         title_font = ImageFont.truetype(font_selif_path, title_font_size)
@@ -65,7 +65,7 @@ def create_card_image(model_no, img_bytearray, option_dict):
 
     card_imgdraw.text((TITLE_LT_XY[0], int((TITLE_LT_XY[1] + TITLE_RB_XY[1]) / 2)), option_dict['タイトル'], fill='black', font=title_font, anchor='lm')
 
-    # 説明文埋め込み
+    # Embedding the Description Text
     description_font = ImageFont.truetype(font_sanselif_path, 40)
 
     description_list = []
@@ -83,9 +83,9 @@ def create_card_image(model_no, img_bytearray, option_dict):
 
     card_imgdraw.text(DESCRIPTION_LT_XY, description_display, fill='black', font=description_font)
 
-    # バイナリデータの出力
+    # Outputting Binary Data
     output_img_bytearray = BytesIO()
     card_img.convert('RGB').save(output_img_bytearray, "JPEG", quality=95)
-    output_img_bytearray.seek(0) # 画像の先頭にシークしないと空データになってしまう。
+    output_img_bytearray.seek(0) # Seek to the beginning of the image, otherwise it results in empty data
 
     return output_img_bytearray

src/front_card_image_historic_site.py

@@ -1,7 +1,9 @@
 from PIL import Image, ImageDraw, ImageFont
 from io import BytesIO
 
-# カード画像関連
+# Card image information
+
+# Historic Site Card files
 card_frame_path_dict = {
     '橙': 'data/cards/史跡カードフレーム(橙).png',
     '白': 'data/cards/史跡カードフレーム(白).png',
@@ -25,38 +27,37 @@ card_mark_path_dict = {
     '都指定': 'data/cards/史跡カード指定マーク(都指定).png'
 }
 
-# カード画像各領域のピクセル位置情報
-# 写真
+# Pixel position information for each area of the card image
+# Picture
 PICTURE_LT_XY = (65, 188)
 PICTURE_RB_XY = (802, 925)
 PICTURE_SIZE = (PICTURE_RB_XY[0] - PICTURE_LT_XY[0], PICTURE_RB_XY[1] - PICTURE_LT_XY[1])
 
-# タイトル
-# ある程度の余白を作る。
+# Title
+# Create some margin
 TITLE_LT_XY = (65, 45) 
-TITLE_RB_XY = (647, 132) # マーク挿入部分と重ならないような位置
+TITLE_RB_XY = (647, 132) # Position to avoid overlapping with the marker insertion point
 TITLE_SIZE = (TITLE_RB_XY[0] - TITLE_LT_XY[0], TITLE_RB_XY[1] - TITLE_LT_XY[1])
 
-# 説明欄区切り線
+# Explanation Section Divider
 DESCRIPTION_LINE_L_XY = (52, 1024)
 DESCRIPTION_LINE_R_XY = (816, 1024)
 
-# 史跡種類
+# Historic Site Type
 HS_TYPE_LT_XY = (56, 972)
 
-# 訪問難度
+# Difficulty of Visit
 DIFFICULTY_LT_XY = (444, 972)
 
-# 説明文本体
+# Main Body of Description
 DESCRIPTION_LT_XY = (46, 1024)
 DESCRIPTION_RB_XY = (810, 1174)
 DESCRIPTION_SIZE = (DESCRIPTION_RB_XY[0] - DESCRIPTION_LT_XY[0], DESCRIPTION_RB_XY[1] - DESCRIPTION_LT_XY[1])
 
-
-# フォント関連
-# 明朝体
+# Font information
+# Ming Typeface
 font_selif_path = 'data/fonts/SourceHanSerif-Bold.otf'
-# ゴシック体
+# Gothic Typeface
 font_sanselif_path = 'data/fonts/SourceHanSans-Bold.otf'
 
 def crop_center(pil_img, crop_width, crop_height):
@@ -71,36 +72,35 @@ def crop_max_square(pil_img):
     
 def create_historic_site_card_image(img_bytearray, option_dict):
 
-    # 画像の読み込みとトリミング
+    # Loading and Cropping of Picture
     picture_img = Image.open(img_bytearray)
     picture_img = crop_max_square(picture_img)
     picture_img = picture_img.resize(PICTURE_SIZE)
 
-
-    # カードの読み込み
+    # Loading of Card Frame
     card_img = Image.open(card_frame_path_dict[option_dict['色']])
 
-    # マークの追加
+    # Adding a Marker
     mark_image = Image.open(card_mark_path_dict[option_dict['マーク']])
     card_img.paste(mark_image, mask=mark_image)
 
-    # 写真の埋め込み
+    # Embedding a Picture in the Card
     card_img.paste(picture_img, PICTURE_LT_XY)
 
-    # 各種書き込み準備
+    # Preparing for editting the card image
     card_imgdraw = ImageDraw.Draw(card_img)
 
-    # カード枠線の追加
+    # Adding a Border to the Card
     card_imgdraw.line(( (0, 0), (card_img.size[0], 0) ), fill='black', width=15)
     card_imgdraw.line(( (0, 0), (0, card_img.size[1]) ), fill='black', width=15)
     card_imgdraw.line(( (card_img.size[0], 0),  card_img.size), fill='black', width=15)
     card_imgdraw.line(( (0, card_img.size[1]),  card_img.size), fill='black', width=15)
 
-    # 説明欄区切り線の追加
+    # Adding a Divider Line to the Explanation Section
     card_imgdraw.line((DESCRIPTION_LINE_L_XY, DESCRIPTION_LINE_R_XY), fill='black', width=3)
 
-    # タイトル埋め込み
-    # (複数行対応は必要ならば対応)
+    # Embedding the Title
+    # (Support for multiple lines if needed)
     title_font_size = 100
     while True:
         title_font = ImageFont.truetype(font_selif_path, title_font_size)
@@ -112,19 +112,19 @@ def create_historic_site_card_image(img_bytearray, option_dict):
 
     card_imgdraw.text((TITLE_LT_XY[0], int((TITLE_LT_XY[1] + TITLE_RB_XY[1]) / 2)), option_dict['タイトル'], fill='black', font=title_font, anchor='lm')
 
-    # 史跡種類埋め込み
+    # Embedding the Historic Site Type
     hs_type_display = f'種類：{option_dict["史跡種類"]}'
     hs_typefont = ImageFont.truetype(font_sanselif_path, 40)
     card_imgdraw.text(HS_TYPE_LT_XY, hs_type_display, fill='black', font=hs_typefont, anchor='lt')
 
-    # 訪問難度埋め込み
+    # Embedding the Difficulty of Visit
     difficulty = int(option_dict['訪問難度'])
     difficulty = 1 if difficulty < 1 else 5 if difficulty > 5 else difficulty
     difficulty_display = '訪問難度:' + '☆' * difficulty + '★' * (5 - difficulty)
     difficulty_font = ImageFont.truetype(font_sanselif_path, 40)
     card_imgdraw.text(DIFFICULTY_LT_XY, difficulty_display, fill='black', font=difficulty_font, anchor='lt')
 
-    # 説明文埋め込み
+    # Embedding the Description Text
     description_font = ImageFont.truetype(font_sanselif_path, 40)
 
     description_list = []
@@ -142,9 +142,9 @@ def create_historic_site_card_image(img_bytearray, option_dict):
 
     card_imgdraw.text(DESCRIPTION_LT_XY, description_display, fill='black', font=description_font)
 
-    # バイナリデータの出力
+    # Outputting Binary Data
     output_img_bytearray = BytesIO()
     card_img.convert('RGB').save(output_img_bytearray, "JPEG", quality=95)
-    output_img_bytearray.seek(0) # 画像の先頭にシークしないと空データになってしまう。
+    output_img_bytearray.seek(0) # Seek to the beginning of the image, otherwise it results in empty data
 
     return output_img_bytearray

src/picture_box_model.py

@@ -1,7 +1,7 @@
 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。
+from PIL import Image as PIL_Image # Renaming to avoid conflict with Image from gltflib
 import struct
 import uuid
 
@@ -9,8 +9,8 @@ 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)
+# Common Binary Information
+# Vertex data(POSITION)
 vertices = [
     [ 1.0,  1.0, -1.0,],
     [ 1.0,  1.0, -1.0,],
@@ -45,7 +45,7 @@ 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)
+# Normal data(NORMAL)
 normals = [
     [ 0.0,  0.0, -1.0,],
     [ 0.0,  1.0, -0.0,],
@@ -78,7 +78,7 @@ for normal in normals:
         normal_bytearray.extend(struct.pack('f', value))
 normal_bytelen = len(normal_bytearray)
 
-# テクスチャ座標(TEXCOORD_0)
+# Texture coordinates(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],
@@ -95,7 +95,7 @@ for texcoord_0 in texcoord_0s:
         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
 vertex_indices = [
      1, 14, 20,
      1, 20,  7,
@@ -118,10 +118,10 @@ vertex_index_bytelen = len(vertex_index_bytearray)
 
 def create_picture_box_model(img_bytearray):
 
-    # 画像の取得
+    # Loading Picture
     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
+    # Adjusting to a Value That Is Divisible by 8 for Edge Length
     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)))
@@ -142,11 +142,11 @@ def create_picture_box_model(img_bytearray):
     img_bytearray = img_bytearray.getvalue()
     img_bytelen = len(img_bytearray)
 
-    # 3Dモデルのスケールの計算
+    # Calculating the Scale of a 3D Model
     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
+    # Concatenation of the binary data section
     bytearray_list = [
         vertex_bytearray,
         normal_bytearray,
@@ -167,20 +167,19 @@ def create_picture_box_model(img_bytearray):
     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
+    offset_list = [0] + bytelen_cumsum_list # The first offset is 0
+    offset_list.pop() # Remove the end
 
-    # リソースの作成
+    # GLBResource
     resources = [GLBResource(data=all_bytearray)]
 
-    # 各種設定
-    # アセット
+    # Asset
     asset=Asset()
 
-    # バッファ
+    # Buffer
     buffers = [Buffer(byteLength=len(all_bytearray))]
 
-    # バッファビュー
+    # BufferView
     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),
@@ -189,7 +188,7 @@ def create_picture_box_model(img_bytearray):
         BufferView(buffer=0, byteOffset=offset_list[4], byteLength=bytelen_list[4], target=None),
     ]
 
-    # アクセサー
+    # Accessor
     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),
@@ -197,20 +196,20 @@ def create_picture_box_model(img_bytearray):
         Accessor(bufferView=3, componentType=ComponentType.UNSIGNED_SHORT.value, count=len(vertex_indices), type=AccessorType.SCALAR.value, max=None, min=None)
     ]
 
-    # イメージ
+    # Image
     images=[
         Image(mimeType='image/jpeg', bufferView=4),
     ]
 
-    # サンプラー
+    # Sampler
     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
+    # Texture
     textures = [
         Texture(name='Image',sampler=0,source=0),
     ]
 
-    # マテリアル
+    # Material
     materials = [
         Material(
             pbrMetallicRoughness=PBRMetallicRoughness(
@@ -224,17 +223,17 @@ def create_picture_box_model(img_bytearray):
         ),
     ]
 
-    # メッシュ
+    # Mesh
     meshes = [
         Mesh(name='Image', primitives=[Primitive(attributes=Attributes(POSITION=0, NORMAL=1,TEXCOORD_0=2),indices=3, material=0)]),
     ]
 
-    # ノード
+    # Node
     nodes = [
         Node(mesh=0,rotation=None, scale=scale),
     ]
 
-    # シーン
+    # Scene
     scene = 0
     scenes = [Scene(name='Scene', nodes=[0])]