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[account]
appId="1nt7j0w17ecd9duruc48m7050012r5a8"
appSecret="1nt7j0w17ecd9duruc48m70600m2a32r"
shopId="1"
[oss]
AccessKeyId = "LTAI5tSReWm8hz7dSYxxth8f"
AccessKeySecret = "8ywTDF9upPAtvgXtLKALY2iMYHIxdS"
EndPoint = "oss-cn-shanghai.aliyuncs.com"
BucketSuwa3dDataSecret = "suwa3d-securedata"
[api]
#请求的域名
#test_domain="http://127.0.0.1:8188/"
domain = "https://open.api.suwa3d.com/"
#Token地址
getToken="token/getToken"
#获取pid
getPid="link/pid"
#记录拍照订单信息
recordPose="link/recordBaseInfo"
#脸部图片的上传地址
faceUploadUrl = "upload/getUploadUrlForBadge"
#下单接口
order = "order/confirmCartAndOrder"
#提交建模
submitModeling = "modeling/submitOrderModeling"
#模拟图片上传回调
callbackImageUpload = "callback/uploadBadgeImage"
[customer]
id=1
peoples=1
props=0
pets=0
people_pose=["站姿"]
platform=99
customer_name="董长希",
customer_mobile="18950403426"
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import utils,time,os,sys
from utils import cfg
#获取PID,记录基础信息
def getPidRecordPose():
params = {
"photo_group_id":int(time.time()),
"customer_id":cfg("customer.id"),
"platform":cfg("customer.platform"),
}
url = cfg("api.domain")+cfg("api.getPid")
data,status = utils.requestUrl(url,"GET",params)
if status != "success":
return 0,"获取PID失败"
pid = data["pid"]
#记录基础信息
params = {
"pid":pid,
"shop_id":cfg("account.shopId"),
"peoples":cfg("customer.peoples"),
"props":cfg("customer.props"),
"pets":cfg("customer.pets"),
"people_pose":cfg("customer.people_pose"),
}
url = cfg("api.domain")+cfg("api.recordPose")
data,status = utils.requestUrl(url,"POST",params)
if status != "success":
return 0,"记录基础信息失败"
print(f"记录基础信息成功,PID:{pid}")
return pid,"success"
#获取照片上传的地址, 上传到脸部位置,上传到卡通图片的位置,
def uploadImages(pid,imagePath):
#检测文件图片是否存在
if not os.path.exists(imagePath):
return "文件不存在"
ossFacePath = f"photos/{pid}/cartoon/origin/face.jpg"
ossPath = f"photos/{pid}/cartoon/cartoon_image/1.png"
utils.oss().put_object_from_file(ossFacePath,imagePath)
utils.oss().put_object_from_file(ossPath,imagePath)
callbackImageUpload(pid)
return "success"
#下单
def makeOrder(pid):
if pid == 0:
return "PID不能为0"
params = {
"pid":pid,
"shop_id":cfg("account.shopId"),
"address":{
"country_id":350206,
"province_id":350000,
"county_id":"0",
"city_id":350200,
"address":"汇金湖里大厦B栋312",
"receive_address":"汇金湖里大厦B栋312",
"send_model_type": 2,
"memo": "测试",
"customer_name": cfg("customer.name"),
"customer_mobile": cfg("customer.mobile")
},
"order_params": [
{
"id": 0,
"discount_name": "",
"discount_amount": 0,
}
],
"carts_info": [
{
"prod_id": 7,
"skus": [
{
"quantity": 1,
"attrs": [
{
"attr_id": 5,
"attr_val_id": 13,
},
{
"attr_id": 1,
"attr_val_id": 1,
}
],
}
]
}
],
"cartoon_pic_no": 1,
"product_name": "badge",
"platform": 99
}
url = cfg("api.domain")+cfg("api.order")
data,status = utils.requestUrl(url,"POST",params)
print(f"下订单结果:{data}")
if status != "success":
return 0,"下单失败"
status = submitModeling(data["order_ids"][0])
if status != "success":
return 0,"提交建模失败"
return data["order_ids"][0],"success"
#图片上传回调
def callbackImageUpload(pid):
params = {
"pid":pid,
"token":utils.getToken(),
}
url = cfg("api.domain")+cfg("api.callbackImageUpload")
data,status = utils.requestUrl(url,"GET",params)
print(f"图片上传回调结果:{data}-{status}")
return "success"
#提交建模
def submitModeling(orderId):
if orderId == 0:
return "订单ID不能为0"
params = {
"order_id":orderId,
"is_cartoon":1,
}
url = cfg("api.domain")+cfg("api.submitModeling")
data,status = utils.requestUrl(url,"POST",params)
print(f"提交建模结果:{status}")
if status != "success":
return "提交建模失败"
return "success"
def imageFolder():
#判断目录下是否有images文件夹 和 文件
if not os.path.exists("images"):
print("images目录不存在")
return
arrFiles = os.listdir("images")
if len(arrFiles) == 0:
print("images目录下没有文件")
return
#遍历 images 目录下的所有图片
for image in arrFiles:
#获取完整的图片地址
imagePath = os.path.join("images",image)
main(imagePath)
def main(imagePath = ""):
#判断文件是否存在
if not os.path.exists(imagePath):
print(f"图片不存在:{imagePath}")
return None,False
print(f"开始处理图片:{imagePath}")
pid,status = getPidRecordPose()
if status != "success":
print(f"获取PID失败:{imagePath}")
return None,False
status = uploadImages(pid,imagePath)
if status != "success":
print(f"上传图片失败:{imagePath}")
return None,False
order_id,status = makeOrder(pid)
if status != "success":
print(f"下单失败:{imagePath}")
return None,False
data = {"pid":pid,"imagePath":imagePath,"orderId":order_id}
print(f"下单成功:{data},移除图片:{imagePath}")
os.remove(imagePath)
return data,True
if __name__ == "__main__":
#获取请求参数
args = sys.argv[1:]
if len(args) == 0:
#需要二次确认是否要处理images目录下的所有图片
confirmV = input("是否要处理images目录下的所有图片? (y/n)")
if confirmV == "y":
imageFolder()
else:
print("请输入图片路径")
sys.exit(1)
else:
for imagePath in args:
main(imagePath)
print(f"{args}")
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xdezmm0291gd9x7z89yj3um2709r55mu|1747365162
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import toml,time,hmac,hashlib,requests
import oss2,os
#读取配置文件
def cfg(keyName):
try:
with open('config.toml', 'r') as f:
config = toml.load(f)
if "." in keyName:
keyName = keyName.split(".")
return config[keyName[0]][keyName[1]]
else:
return config[keyName]
except Exception as e:
return None
#生成签名
def sign(params):
params = [
f"appId={params['appId']}",
f"appSecret={cfg('account.appSecret')}",
f"shopId={params['shop_id']}",
f"timestamp={params['timestamp']}"
]
# 拼接参数字符串
joined_str = "&".join(params)
#进行签名 签名方式采用 HMAC-SHA256 算法
hmac_sha256 = hmac.new(cfg("account.appSecret").encode(), joined_str.encode(), hashlib.sha256)
sign = hmac_sha256.hexdigest()
return sign
#获取token
def getToken():
#判断是否有token.txt文件
if os.path.exists("token.txt"):
#读取token.txt文件
with open("token.txt", "r") as f:
token = f.read()
#判断token是否过期
if int(token.split("|")[1]) > int(time.time()):
return token.split("|")[0]
#获取token
url = cfg("api.domain")+cfg("api.getToken")
params = {
"appId":cfg("account.appId"),
"shop_id":cfg("account.shopId"),
"timestamp":str(int(time.time())), #时间戳,秒级 Unix 时间戳(自 1970-01-01 00:00:00 UTC 以来的秒数), 10位数
}
params["sign"] = sign(params)
#发送请求
response = requests.post(url, json=params)
data = response.json()
if data["code"] != 1000:
print("获取token失败",data)
return ""
else:
#记录token
with open("token.txt", "w") as f:
f.write(data["data"]["token"]+"|"+str(int(time.time())+3600))
return data["data"]["token"]
def requestUrl(url,method,params):
#获取token
token = getToken()
#设置headers
headers = {
"Authorization":f"Bearer {token}",
"Content-Type":"application/json"
}
#发送请求
response = requests.request(method,url,headers=headers,json=params)
data = response.json()
if data["code"] != 1000:
print("请求失败",data)
return "","error"
else:
return data["data"],"success"
def oss():
AccessKeyId = cfg("oss.AccessKeyId")
AccessKeySecret = cfg("oss.AccessKeySecret")
Endpoint = cfg("oss.EndPoint")
Bucket = cfg("oss.BucketSuwa3dDataSecret")
oss_client = oss2.Bucket(oss2.Auth(AccessKeyId, AccessKeySecret), Endpoint, Bucket)
return oss_client
+20 -11
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@@ -86,9 +86,8 @@ 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)
pid_file_dir = os.path.join(args.input,pid)
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:
@@ -104,7 +103,6 @@ def rander_image_and_check(args):
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()
@@ -124,12 +122,12 @@ def rander_image_and_check(args):
# 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, obj_file))
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))
bpy.ops.import_scene.obj(filepath=os.path.join(args.input, pid, 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)
texture_path = os.path.join(args.input, pid, texture_file)
materials = bpy.data.materials
for material in materials:
# 确保材质使用节点树
@@ -145,7 +143,17 @@ def rander_image_and_check(args):
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]
min_z = min(corner.z for corner in bbox_corners)
bpy.ops.object.select_all(action='DESELECT')
imported_object.select_set(True)
bpy.context.view_layer.objects.active = imported_object
# Move object down so lowest point is at origin
imported_object.location.z -= min_z
# Apply transformations
bpy.ops.object.transform_apply(location=True, rotation=True, scale=True)
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)
@@ -223,8 +231,10 @@ def rander_image_and_check(args):
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)
png_name = f"{pid}_{column + 1}.png"
png_out_path = os.path.join(args.output, args.len_type,
f'{pid}_{args.resolution_x}x{args.resolution_y}_{args.ps_column}',
camera_id, png_name)
bpy.context.scene.render.filepath = png_out_path
bpy.context.scene.render.image_settings.file_format = 'PNG'
@@ -246,7 +256,7 @@ def rander_image_and_check(args):
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('-pid', '--pid', type=str, default='236479', 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/',
@@ -258,7 +268,7 @@ def get_args():
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',
argparser.add_argument('-e', '--Env_Texture_path', type=str, default='/data/datasets/hdrs/studio_small_08_2k.exr',
help='enviroment texture path')
args = argparser.parse_args()
@@ -285,7 +295,6 @@ def rander_image_run(args):
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)
@@ -0,0 +1,302 @@
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, 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
"""