import math, os, time, sys, bpy, argparse from tqdm import tqdm from contextlib import contextmanager from mathutils import Vector from PIL import Image import numpy as np @contextmanager def stdout_redirected(to=os.devnull): ''' import os with stdout_redirected(to=filename): print("from Python") os.system("echo non-Python applications are also supported") ''' fd = sys.stdout.fileno() ##### assert that Python and C stdio write using the same file descriptor ####assert libc.fileno(ctypes.c_void_p.in_dll(libc, "stdout")) == fd == 1 def _redirect_stdout(to): sys.stdout.close() # + implicit flush() os.dup2(to.fileno(), fd) # fd writes to 'to' file sys.stdout = os.fdopen(fd, 'w') # Python writes to fd with os.fdopen(os.dup(fd), 'w') as old_stdout: with open(to, 'w') as file: _redirect_stdout(to=file) try: yield # allow code to be run with the redirected stdout finally: _redirect_stdout(to=old_stdout) # restore stdout. # buffering and flags such as # CLOEXEC may be different def check_image_rander(png_image_dir): """检查图片生成是否正常""" image_list = os.listdir(png_image_dir) if len(image_list)>0: image_path = os.path.join(png_image_dir,image_list[0]) img = Image.open(image_path) # 将图像转换为 RGB 模式 img = img.convert("RGB") # 将图像数据转换为 numpy 数组 img_data = np.array(img) # 设定颜色分段数 color_bins = 24 # 将颜色分成 24 种，计算颜色区间 # 对每个 RGB 值进行分段 def get_color_bin(value, bins): return (value * bins) // 256 # 用于存储所有颜色的集合 color_set = set() # 遍历图像每一个像素 for row in img_data: for pixel in row: # 将 RGB 每个通道的值分段 r, g, b = pixel r_bin = get_color_bin(r, color_bins) g_bin = get_color_bin(g, color_bins) b_bin = get_color_bin(b, color_bins) # 将 RGB 分段后的颜色组合成一个元组 color_set.add((r_bin, g_bin, b_bin)) # 输出不同的颜色数量 print(f"该图像中有 {len(color_set)} 种颜色。") if len(color_set)>20: return True else: return False else: return False def rander_image_and_check(args): """渲染图片""" # 列出obj列表 pid = args.pid pid_file_dir = os.path.join(args.input) if not os.path.exists(pid_file_dir): print(f"{pid_file_dir} 文件夹不存在") return obj_file_list = [aa for aa in os.listdir(pid_file_dir) if aa.endswith(".obj")] if len(obj_file_list)==0: print("没有obj文件",pid) return texture_path_list = [aa for aa in os.listdir(pid_file_dir) if aa.endswith(".jpg")] if len(texture_path_list)==0: print("没有贴图文件",pid) return texture_file = texture_path_list[0] sorted_obj_file_list = sorted(obj_file_list, key=len) print(sorted_obj_file_list) is_rander = False # 根据obj表渲染图片 for obj_file in sorted_obj_file_list: print(f"开始执行blender渲染--{obj_file}") start = time.time() # 初始化blender环境 bpy.ops.wm.read_homefile() bpy.ops.object.delete(use_global=False, confirm=False) bpy.context.scene.unit_settings.scale_length = 1 bpy.context.scene.unit_settings.length_unit = 'CENTIMETERS' bpy.context.scene.unit_settings.mass_unit = 'GRAMS' # bpy.context.scene.render.engine = 'CYCLES' bpy.context.scene.render.engine = 'BLENDER_EEVEE' # ('BLENDER_EEVEE', 'BLENDER_WORKBENCH', 'CYCLES') bpy.context.scene.cycles.feature_set = 'SUPPORTED' bpy.context.scene.cycles.device = 'GPU' bpy.context.scene.cycles.preview_samples = args.sample bpy.context.scene.cycles.samples = args.sample bpy.context.scene.render.film_transparent = True bpy.context.scene.cycles.use_progressive_refining = True # 启用渐进式渲染 # 导入模型文件 print(f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())}: import pid: {pid}') start_import = time.time() print("===============", os.path.join(args.input, pid, obj_file)) with stdout_redirected(to=os.devnull): bpy.ops.import_scene.obj(filepath=os.path.join(args.input,obj_file)) print( f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())}: import pid: {pid} done in {time.time() - start_import:.2f}s') texture_path = os.path.join(args.input,texture_file) materials = bpy.data.materials for material in materials: # 确保材质使用节点树 if not material.use_nodes: material.use_nodes = True node_tree = material.node_tree texture_node = node_tree.nodes.new(type='ShaderNodeTexImage') texture_node.image = bpy.data.images.load(texture_path) bsdf_node = node_tree.nodes.get('Principled BSDF') if bsdf_node: node_tree.links.new(bsdf_node.inputs['Base Color'], texture_node.outputs['Color']) # 获取模型对象 imported_object = bpy.context.selected_objects[0] # 假设只导入一个模型 # 获取模型的边界框（bounding box） bbox_corners = [imported_object.matrix_world @ Vector(corner) for corner in imported_object.bound_box] # 获取最高点的 Y 值 model_height = max(corner.z for corner in bbox_corners) print(f"The highest Y value of the model is: {model_height}") # 获取相机的位置 (假设相机位置参数已经在args中设定) camera_position = args.cameras['1']['position'] # 计算缩放比例：假设模型的高度是1米（或者你可以通过其他方法计算模型的实际高度） # model_height =25 # 这是一个假设值，实际应用中需要根据模型大小来设定 scale_factor = camera_position / model_height # 根据相机高度和模型高度计算缩放比例 bpy.context.view_layer.objects.active = imported_object imported_object.select_set(True) bpy.ops.object.align(align_mode='OPT_1', relative_to='OPT_1', align_axis={'Z'}) bpy.ops.object.transform_apply(location=True, rotation=True, scale=True) # 设置模型的缩放 imported_object.scale = (scale_factor, scale_factor, scale_factor) bpy.context.object.rotation_euler = (0, 0, 0) bpy.ops.object.origin_set(type='ORIGIN_CENTER_OF_VOLUME', center='MEDIAN') bpy.context.object.location[0] = 0 # 移动到特定位置(1m, 1m)是为了让human3d可以正确识别 bpy.context.object.location[1] = 0 bpy.ops.object.transform_apply(location=True, rotation=True, scale=True) # 设置环境光 bpy.data.scenes['Scene'].world.use_nodes = True enode = bpy.data.scenes['Scene'].world.node_tree.nodes.new("ShaderNodeTexEnvironment") enode.image = bpy.data.images.load(args.Env_Texture_path) bpy.data.scenes['Scene'].world.node_tree.links.new(enode.outputs['Color'], bpy.data.scenes['Scene'].world.node_tree.nodes[ 'Background'].inputs['Color']) # 初始化相机 camera_lens = 9 # 相机焦距，调整焦距改变镜头广角角度覆盖视野范围 camera_sensor_width = 25.4 # 相机传感器宽度 1英寸 = 25.4mm camera_angle = 2 * math.pi / args.ps_column # 每台相机的圆心角（弧度） # 初始相机参数 bpy.ops.object.select_all(action='DESELECT') obj_camera = bpy.data.objects['Camera'] bpy.context.view_layer.objects.active = obj_camera obj_camera.select_set(True) bpy.context.object.data.type = args.len_type bpy.context.object.data.sensor_width = camera_sensor_width bpy.context.scene.render.resolution_x = args.resolution_x bpy.context.scene.render.resolution_y = args.resolution_y obj_camera.name = 'camera_init' # 计算并输出所有相机的坐标和旋转 for column in tqdm(range(args.ps_column)): theta = (column + 1) * camera_angle x = args.ps_radius * math.sin(theta) y = args.ps_radius * math.cos(theta) for camera_id, camera_info in args.cameras.items(): x_ble = x y_ble = y z_ble = camera_info['position'] camera_copy_name = obj_camera.copy() camera_copy_name.data = obj_camera.data.copy() bpy.context.collection.objects.link(camera_copy_name) bpy.ops.object.select_all(action='DESELECT') bpy.context.view_layer.objects.active = camera_copy_name camera_copy_name.select_set(True) camera_copy_name.name = f"camera_{column + 1}_{camera_id}" if args.len_type == 'PERSP': bpy.context.object.data.lens = camera_info['PERSP_lens'] elif args.len_type == 'ORTHO': bpy.context.object.data.ortho_scale = camera_info['ORTHO_scale'] camera_copy_name.location = (x_ble, -y_ble, z_ble) camera_copy_name.rotation_euler = (camera_info['rotation'], 0, theta) # 渲染图片 bpy.context.scene.camera = bpy.data.objects[camera_copy_name.name] # 切换当前相机 os.makedirs(os.path.join(args.output, args.len_type, f'{pid}_{args.resolution_x}x{args.resolution_y}_{args.ps_column}', camera_id), exist_ok=True) png_name = f"{pid}_pic.png" png_out_path = os.path.join(args.output,png_name) bpy.context.scene.render.filepath = png_out_path bpy.context.scene.render.image_settings.file_format = 'PNG' with stdout_redirected(): bpy.ops.render.render(write_still=True) # delete camera_init bpy.data.objects.remove(bpy.context.scene.objects['camera_init']) bpy.data.objects.remove(bpy.context.scene.objects['Light']) bpy.ops.wm.quit_blender() print(f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())}: render pid: {pid} done, time: {time.time() - start:.2f}s') png_image_dir = os.path.join(args.output, args.len_type,f'{pid}_{args.resolution_x}x{args.resolution_y}_{args.ps_column}',"1",) time.sleep(2) if os.path.exists(png_image_dir): if check_image_rander(png_image_dir): break def get_args(): argparser = argparse.ArgumentParser(description='Render the camera in the studio') argparser.add_argument('-pid', '--pid', type=str, default='', help='pid of the model') argparser.add_argument('-i', '--input', type=str, default='/data/datasets_20t/obj_rander/', help='input models path') argparser.add_argument('-o', '--output', type=str, default='/data/datasets_20t/render_images/', help='output images path') argparser.add_argument('-l', '--limit', type=int, default=0, help='render limit') argparser.add_argument('-ps_radius', '--ps_radius', type=float, default='18', help='photo studio radius, unit: m') argparser.add_argument('-ps_column', '--ps_column', type=int, default='1', help='photo studio column number') argparser.add_argument('-t', '--len_type', type=str, default='ORTHO', help='camera lens type, PERSP or.ORTHO') argparser.add_argument('-r_x', '--resolution_x', type=int, default='768', help='render resolution_x') argparser.add_argument('-r_y', '--resolution_y', type=int, default='1024', help='render resolution_y') argparser.add_argument('-s', '--sample', type=int, default='512', help='render sample') argparser.add_argument('-e', '--Env_Texture_path', type=str, default='D://make2/tools/pic_for_obj/hdrs/studio_small_08_2k.exr', help='enviroment texture path') args = argparser.parse_args() # 相机参数，人体按2米身高，多人拍照覆盖设置 args.cameras = { '1': { 'position': 2.5, # 1号相机的位置 0.9米高 'rotation': math.radians(86), 'PERSP_lens': 8, 'ORTHO_scale': 3.0, }, # '2': { # 'position': 1.8 , # 2号相机的位置 1.8米高 # 'rotation': math.radians(58), # 'PERSP_lens': 13, # 'ORTHO_scale': 2.5, # } } return args def rander_image_run(args): """主流程""" if not os.path.exists(args.output): os.makedirs(args.output) try: print("进入渲染") rander_image_and_check(args) except : print("图片渲染错误",args.pid) if __name__ == '__main__': args = get_args() rander_image_run(args) #python image_rander_small.py -pid 234161 -i /data/datasets_20t/obj_rander/ -o /data/datasets_20t/render_images/ # python image_rander_small.py -pid 5924 -i /data/datasets_20t/obj_rander/ -o /data/datasets_20t/render_images/ """ argparser.add_argument('-e', '--Env_Texture_path', type=str, default='/data/datasets/hdrs/studio_small_08_2k.exr', 替换成自己的hdrs路径 bpy 3.4.0 """