487 lines
23 KiB
Python
487 lines
23 KiB
Python
import os, sys, bpy, math, time, platform, cairosvg, ppf.datamatrix, shutil, requests, json, redis, oss2, cv2
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from retrying import retry
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import numpy as np
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import matplotlib.pyplot as plt
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from PIL import Image, ImageEnhance
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from addon_utils import enable
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import logging
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logging.basicConfig(filename='foot_update_res.log', level=logging.ERROR)
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enable('io_import_images_as_planes')
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enable('eyek_addon')
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def gen_data_matrix(print_id, qr_path, size = 300):
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svg = ppf.datamatrix.DataMatrix(f'p{print_id}').svg()
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cairosvg.svg2png(bytestring=svg, write_to=qr_path, output_width=size, output_height=size, background_color='white')
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def active_object(obj):
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bpy.context.view_layer.objects.active = obj
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obj.select_set(True)
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@retry(stop_max_attempt_number=10, wait_fixed=2000)
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def down_obj_fromoss(pid, print_type=1, order_id=None):
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# print_type：// 打印状态 1:正常打印 2:重打 3:加打，4: 样品
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print(f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())} pid: {pid} 开始下载模型，若网络异常将每间隔2秒重试10次...')
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if not order_id is None:
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path = os.path.join(workdir, f'{pid}_{order_id}')
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else:
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path = os.path.join(workdir, pid)
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if os.path.exists(path):
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print(f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())} pid: {pid} 已存在模型文件，删除后重新下载')
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shutil.rmtree(path, ignore_errors=True)
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os.makedirs(path)
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# 下载分2种情况，一种是第一次打印，下载标准{pid}.obj,{pid}.mtl,{pid}Tex1.jpg，另一种是重打或加打，obj文件名可以从oss上任意获取一个，但是mtl和jpg文件名是固定的
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res = oss_client.get_object_to_file(f'objs/print/{pid}/{pid}.mtl', os.path.join(path, f'{pid}.mtl'))
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last_modified = oss_client.get_object_meta(f"objs/print/{pid}/{pid}.mtl").last_modified
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print(f'mtl文件最后修改时间：{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(last_modified))}')
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print(f'下载文件：objs/print/{pid}/{pid}.mtl，状态：{res.status}')
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if oss_client.object_exists(f'objs/print/{pid}/{pid}Tex1.jpg'):
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res = oss_client.get_object_to_file(f'objs/print/{pid}/{pid}Tex1.jpg', os.path.join(path, f'{pid}Tex1.jpg'))
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last_modified = oss_client.get_object_meta(f"objs/print/{pid}/{pid}Tex1.jpg").last_modified
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print(f'jpg文件最后修改时间：{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(last_modified))}')
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print(f'下载文件：objs/print/{pid}/{pid}Tex1.jpg，状态：{res.status}')
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else:
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res = oss_client.get_object_to_file(f'objs/print/{pid}/{pid}.jpg', os.path.join(path, f'{pid}Tex1.jpg'))
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last_modified = oss_client.get_object_meta(f"objs/print/{pid}/{pid}.jpg").last_modified
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print(f'jpg文件最后修改时间：{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(last_modified))}')
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print(f'下载文件：objs/print/{pid}/{pid}.jpg，状态：{res.status}')
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if oss_client.object_exists(f'objs/print/{pid}/{pid}.obj'):
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res = oss_client.get_object_to_file(f'objs/print/{pid}/{pid}.obj', os.path.join(path, f'{pid}.obj'))
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last_modified = oss_client.get_object_meta(f"objs/print/{pid}/{pid}.obj").last_modified
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print(f'obj文件最后修改时间：{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(last_modified))}')
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print(f'下载文件：objs/print/{pid}/{pid}.obj，状态：{res.status}')
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else:
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prefix = f'objs/print/{pid}/'
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filelist = oss2.ObjectIteratorV2(oss_client, prefix=prefix)
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for file in filelist:
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filename = file.key.split('/')[-1]
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if filename == '': continue
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if filename.endswith(f'.obj'):
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res = oss_client.get_object_to_file(file.key, os.path.join(path, f'{pid}.obj'))
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last_modified = oss_client.get_object_meta(file.key).last_modified
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print(f'obj文件最后修改时间：{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(last_modified))}')
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print(f'下载文件：{file.key}，状态：{res.status}')
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break
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def find_obj(pid, order_id):
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find = False
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# if not os.path.exists(os.path.join(workdir, f'{pid}_{order_id}', f'{pid}.mtl')):
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# print('没有找到obj模型文件，开始下载')
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down_obj_fromoss(pid, order_id=order_id)
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if os.path.exists(os.path.join(workdir, f'{pid}_{order_id}', f'{pid}.jpg')):
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shutil.move(os.path.join(workdir, f'{pid}_{order_id}', f'{pid}.jpg'), os.path.join(workdir, f'{pid}_{order_id}', f'{pid}Tex1.jpg'))
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with open(os.path.join(workdir, f'{pid}_{order_id}', f'{pid}.mtl'), 'r') as f:
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lines = f.readlines()
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lines = [line.replace(f'map_Kd {pid}.jpg', f'map_Kd {pid}Tex1.jpg') for line in lines]
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with open(os.path.join(workdir, f'{pid}_{order_id}', f'{pid}.mtl'), 'w') as f:
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f.writelines(lines)
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filelist = os.listdir(os.path.join(workdir, f'{pid}_{order_id}'))
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for filename in filelist:
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if f'{pid}.obj' in filename:
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find = True
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return filename
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print('没有找到obj模型文件')
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return ''
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def find_pid_objname(pid):
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for obj in bpy.data.objects:
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if obj.name.startswith(str(pid)):
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return obj.name
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def ps_color_scale_adjustment(image, shadow=0, highlight=255, midtones=1):
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'''
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模拟 PS 的色阶调整； 0 <= Shadow < Highlight <= 255
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:param image: 传入的图片
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:param shadow: 黑场(0-Highlight)
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:param highlight: 白场(Shadow-255)
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:param midtones: 灰场(9.99-0.01)
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:return: 图片
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'''
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if highlight > 255:
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highlight = 255
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if shadow < 0:
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shadow = 0
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if shadow >= highlight:
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shadow = highlight - 2
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if midtones > 9.99:
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midtones = 9.99
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if midtones < 0.01:
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midtones = 0.01
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image = np.array(image, dtype=np.float16)
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# 计算白场 黑场离差
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Diff = highlight - shadow
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image = image - shadow
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image[image < 0] = 0
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image = (image / Diff) ** (1 / midtones) * 255
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image[image > 255] = 255
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image = np.array(image, dtype=np.uint8)
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return image
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def show_histogram(image, image_id, save_hist_dir, min_threshold, max_threshold):
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'''
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画出直方图展示
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:param image: 导入图片
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:param image_id: 图片id编号
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:param save_hist_dir: 保存路径
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:param min_threshold: 最小阈值
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:param max_threshold: 最大阈值
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:return: 原图image，和裁剪原图直方图高低阈值后的图片image_change
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'''
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plt.rcParams['font.family'] = 'SimHei'
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plt.rcParams['axes.unicode_minus'] = False
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plt.hist(image.ravel(), 254, range=(2, 256), density=False)
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plt.hist(image.ravel(), 96, range=(2, 50), density=False) # 放大 range(0, 50),bins值最好是range的两倍，显得更稀疏，便于对比
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plt.hist(image.ravel(), 110, range=(200, 255), density=False) # 放大 range(225, 255)
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plt.annotate('thresh1=' + str(min_threshold), # 文本内容
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xy=(min_threshold, 0), # 箭头指向位置 # 阈值设定值！
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xytext=(min_threshold, 500000), # 文本位置 # 阈值设定值！
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arrowprops=dict(facecolor='black', width=1, shrink=5, headwidth=2)) # 箭头
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plt.annotate('thresh2=' + str(max_threshold), # 文本内容
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xy=(max_threshold, 0), # 箭头指向位置 # 阈值设定值！
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xytext=(max_threshold, 500000), # 文本位置 # 阈值设定值！
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arrowprops=dict(facecolor='black', width=1, shrink=5, headwidth=2)) # 箭头
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# 在y轴上绘制一条直线
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# plt.axhline(y=10000, color='r', linestyle='--', linewidth=0.5)
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plt.title(str(image_id))
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# plt.show()
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# 保存直方图
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save_hist_name = os.path.join(save_hist_dir, f'{image_id}_{min_threshold}&{max_threshold}.jpg')
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plt.savefig(save_hist_name)
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# 清空画布， 防止重叠展示
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plt.clf()
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def low_find_histogram_range(image, target_frequency):
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'''
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循环查找在 target_frequency (y)频次限制下的直方图区间值(x)
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:param image: 导入图片
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:param target_frequency: 直方图 y 频次限制条件
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:return: 直方图区间 x，和 该区间频次 y
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'''
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# 计算灰度直方图
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hist, bins = np.histogram(image, bins=256, range=[0, 256])
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# 初始化区间和频次
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interval = 2
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frequency = hist[255]
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while frequency < target_frequency:
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# 更新区间和频次
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interval += 1
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# 检查直方图的频次是否为None，如果频次是None，则将其设为0，这样可以避免将None和int进行比较报错。
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frequency = hist[interval] if hist[interval] is not None else 0
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frequency += hist[interval] if hist[interval] is not None else 0
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# 如果频次接近10000则停止循环
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if target_frequency - 2000 <= frequency <= target_frequency + 1000:
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break
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return interval, frequency
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def high_find_histogram_range(image, target_frequency):
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'''
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循环查找在 target_frequency (y)频次限制下的直方图区间值(x)
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:param image: 导入图片
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:param target_frequency: 直方图 y 频次限制条件
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:return: 直方图区间 x，和 该区间频次 y
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'''
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# 计算灰度直方图
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hist, bins = np.histogram(image, bins=256, range=[0, 256])
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# 初始化区间和频次
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interval = 255
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frequency = hist[255]
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while frequency < target_frequency:
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# 更新区间和频次
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interval -= 1
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# 检查直方图的频次是否为None，如果频次是None，则将其设为0，这样可以避免将None和int进行比较报错。
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frequency = hist[interval] if hist[interval] is not None else 0
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frequency += hist[interval] if hist[interval] is not None else 0
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# 如果频次接近10000则停止循环
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if target_frequency - 2000 <= frequency <= target_frequency + 2000:
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break
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return interval, frequency
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def reduce_sharpness(image, factor):
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'''
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使用PIL库减弱图像锐度
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:param image: 图像
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:param factor: 锐度因子，0表示最大程度减弱锐度，1表示原始图像
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:return: 减弱锐度后的图像
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'''
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# OpenCV 格式的图像转换为 PIL 的 Image 对象
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image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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pil_image = Image.fromarray(image_rgb)
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enhancer = ImageEnhance.Sharpness(pil_image)
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reduced_image = enhancer.enhance(factor)
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# PIL 的 Image 对象转换为 OpenCV 的图像格式
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image_array = np.array(reduced_image)
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sharpened_image = cv2.cvtColor(image_array, cv2.COLOR_RGB2BGR)
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return sharpened_image
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def sharpening_filter(image):
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'''
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锐化滤波器对图片进行锐化，增强图像中的边缘和细节
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:param image: 导入图片
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:return: 锐化后的图片
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'''
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sharp_kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
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sharpened_image = cv2.filter2D(image, -1, sharp_kernel)
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return sharpened_image
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def find_last_x(image, slope_threshold = 1000):
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x = []
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y = []
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hist, bins = np.histogram(image, bins=256, range=[0, 256])
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#找到50以内的最高峰
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max_y = 0
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max_i = 5
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for i in range(5, 50):
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if hist[i] > max_y:
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max_y = hist[i]
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max_i = i
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print(f'50以内最高峰值y：{max_y}，最高峰位置x：{max_i}')
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for i in range(2, max_i):
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x.append(i)
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y.append(hist[i])
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slopes = [abs(y[i + 1] - y[i]) for i in range(len(x) - 1)]
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current_interval = []
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max_interval = []
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max_x = {}
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for i, slope in enumerate(slopes):
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current_interval.append(slope)
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if slope >= slope_threshold:
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if len(current_interval) > len(max_interval):
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max_interval = current_interval.copy()
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max_x[x[i]] = slope
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current_interval = []
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print(max_x)
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last_x = list(max_x)[-1]
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last_y = max_x[last_x]
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return last_x, last_y
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def remove_gray_and_sharpening(jpg_path):
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input_image = cv2.imread(jpg_path)
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# low_x_thresh, low_y_frequency = low_find_histogram_range(input_image, low_y_limit)
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low_x_thresh, low_y_frequency = find_last_x(input_image, 1000)
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high_x_thresh, high_y_frequency = high_find_histogram_range(input_image, high_y_limit)
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print(f"{low_x_thresh} 区间, {low_y_frequency} 频次")
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print(f"{high_x_thresh} 区间, {high_y_frequency} 频次")
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high_output_image = ps_color_scale_adjustment(input_image, shadow=low_x_thresh, highlight=high_x_thresh, midtones=1)
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# high_output_image = ps_color_scale_adjustment(low_ouput_image, shadow=0, highlight=high_x_thresh, midtones=1)
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# # 人体贴图和黑色背景交界处不进行锐化
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# gray = cv2.cvtColor(input_image, cv2.COLOR_BGR2GRAY)
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# _, thresh = cv2.threshold(gray, 2, 255, cv2.THRESH_BINARY)
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# kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (7, 7))
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# gradient = cv2.morphologyEx(thresh, cv2.MORPH_GRADIENT, kernel)
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# roi_gradient = cv2.bitwise_and(high_output_image, high_output_image, mask=gradient)
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# # 锐化滤波器
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# # sharpened_image = sharpening_filter(high_output_image)
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# sharpened_image = reduce_sharpness(high_output_image, factor=4)
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# # 将原图边界替换锐化后的图片边界
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# sharpened_image[gradient != 0] = roi_gradient[gradient != 0]
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# 直方图标记并保存
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# show_histogram(input_image, img_id, low_x_thresh, high_x_thresh)
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cv2.imwrite(jpg_path, high_output_image, [cv2.IMWRITE_JPEG_QUALITY, 95]) # 保存图片的质量是原图的 95%
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def main(workdir, r, print_id):
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print('脚底板二维码程序开始运行...')
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only_one = False
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while True:
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if print_id == '0':
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try:
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if r.llen('model:foot') == 0:
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# print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime()), '队列为空，5秒后重试')
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time.sleep(5)
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continue
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except Exception as e:
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print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime()), 'redis连接异常，5秒后重试')
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print(e)
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time.sleep(5)
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r = redis.Redis(host='106.14.158.208', password='kcV2000', port=6379, db=6)
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# r = redis.Redis(host='172.31.1.254', password='', port=6379, db=6)
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continue
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# 打印队列里面的全部内容
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print(f'当前model:foot队列长度：{r.llen("model:foot")}')
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for i in r.lrange('model:foot', 0, -1):
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print(i)
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print_id = r.lpop('model:foot')
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if print_id is None:
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print_id = '0'
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continue
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print_id = print_id.decode('utf-8')
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else:
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print(f'接收到运行一个{print_id}任务')
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only_one = True
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res = requests.get(f'{get_pid_by_printid_url}?print_id={print_id}')
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print('获取pid:', f'{get_pid_by_printid_url}?print_id={print_id}', res.text)
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pid = json.loads(res.text)['data']['pid']
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order_id = json.loads(res.text)['data']['order_id']
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filename = os.path.join(workdir, f'{pid}_{order_id}', find_obj(pid, order_id))
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print('导入obj文件：', filename)
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if only_one:
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print(f'接收到运行一个{print_id}任务，强制调用cal_foot_position.py计算并上传qr_position')
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os.system(f'blender -b -P cal_foot_position.py -- {pid}_{order_id}_{print_id}')
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res = requests.get(f'{get_qr_position_url}?print_id={print_id}')
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print('从云端获取的qr_position:', res.text)
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qr_position = json.loads(res.text)['data']['position_data']
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else:
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#从云端获取qr_position，如果获取为空，调用cal_foot_position.py计算并上传qr_position，再重新读取qr_position.txt
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res = requests.get(f'{get_qr_position_url}?print_id={print_id}')
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print('从云端获取的qr_position:', res.text)
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qr_position = json.loads(res.text)['data']['position_data']
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if qr_position == '':
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print('qr_position为空，调用cal_foot_position.py计算并上传qr_position')
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os.system(f'blender -b -P cal_foot_position.py -- {pid}_{order_id}_{print_id}')
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res = requests.get(f'{get_qr_position_url}?print_id={print_id}')
|
||
print('从云端获取的qr_position:', res.text)
|
||
qr_position = json.loads(res.text)['data']['position_data']
|
||
else:
|
||
qr_position = json.loads(qr_position)
|
||
|
||
if type(qr_position) == str: qr_position = json.loads(qr_position)
|
||
print(f'type of qr_position:{type(qr_position)}')
|
||
print(f'qr_position:{qr_position}')
|
||
|
||
qr_position['location'][2] = -0.1
|
||
# 根据print_id生成qr码
|
||
qr_path = os.path.join(workdir, f'{pid}_{order_id}' ,'qr.png')
|
||
gen_data_matrix(print_id, qr_path)
|
||
|
||
# 导入obj文件，重置到标准单位
|
||
bpy.ops.wm.read_homefile()
|
||
bpy.context.preferences.view.language = 'en_US'
|
||
bpy.ops.object.delete(use_global=False, confirm=False)
|
||
bpy.context.scene.unit_settings.scale_length = 0.001
|
||
bpy.context.scene.unit_settings.length_unit = 'CENTIMETERS'
|
||
bpy.context.scene.unit_settings.mass_unit = 'GRAMS'
|
||
|
||
bpy.ops.import_scene.obj(filepath=filename)
|
||
|
||
obj = bpy.context.selected_objects[0]
|
||
bpy.context.view_layer.objects.active = obj
|
||
obj.select_set(True)
|
||
|
||
pid_objname = find_pid_objname(pid)
|
||
|
||
scale = 90 / obj.dimensions.y
|
||
obj.scale = (scale, scale, scale)
|
||
bpy.ops.object.align(align_mode='OPT_1', relative_to='OPT_1', align_axis={'Z'})
|
||
bpy.ops.object.origin_set(type='ORIGIN_CENTER_OF_MASS', center='MEDIAN')
|
||
obj.location[0] = 0
|
||
obj.location[1] = 0
|
||
bpy.ops.object.transform_apply(location=True, rotation=True, scale=True)
|
||
|
||
print(f'qr_position:{qr_position}')
|
||
print(f'qr_position_type:{type(qr_position)}')
|
||
|
||
# 根据qr_position的值，恢复qr的位置和尺寸，重新生成贴图
|
||
bpy.ops.object.load_reference_image(filepath=os.path.join(workdir, f'{pid}_{order_id}', 'qr.png'))
|
||
bpy.context.object.rotation_euler = (math.radians(-180), math.radians(0), qr_position['rotation'])
|
||
bpy.ops.transform.translate(value=qr_position['location'], orient_type='GLOBAL', orient_matrix=((1, 0, 0), (0, 1, 0), (0, 0, 1)), orient_matrix_type='GLOBAL', mirror=False, use_proportional_edit=False, proportional_edit_falloff='SMOOTH', proportional_size=1, use_proportional_connected=False, use_proportional_projected=False, snap=False, snap_elements={'INCREMENT'}, use_snap_project=False, snap_target='CLOSEST', use_snap_self=True, use_snap_edit=True, use_snap_nonedit=True, use_snap_selectable=False, release_confirm=True)
|
||
|
||
bpy.context.object.empty_display_size = qr_position['dimensions'][0]
|
||
|
||
qr_path = os.path.join(workdir,f'{pid}_{order_id}', f"{pid}_{order_id}Tex1_qr.png")
|
||
jpg_path = os.path.join(workdir,f'{pid}_{order_id}', f"{pid}Tex1.jpg")
|
||
jpg_img = Image.open(jpg_path)
|
||
shutil.copyfile(jpg_path, os.path.join(workdir,f'{pid}_{order_id}', f"{pid}Tex1_noqr.jpg"))
|
||
|
||
bpy.context.scene.eyek.res_x = jpg_img.width
|
||
bpy.context.scene.eyek.res_y = jpg_img.height
|
||
bpy.context.scene.eyek.path_export_image = qr_path
|
||
bpy.data.objects[pid_objname].select_set(True)
|
||
bpy.data.objects['Empty'].select_set(True)
|
||
bpy.context.view_layer.objects.active = bpy.data.objects[pid_objname]
|
||
bpy.ops.eyek.exe()
|
||
|
||
qr_img = Image.open(qr_path)
|
||
jpg_img.paste(qr_img, (0, 0), qr_img)
|
||
jpg_img.save(jpg_path, quality=90)
|
||
shutil.copyfile(jpg_path, os.path.join(workdir,f'{pid}_{order_id}', f"{pid}Tex1_qr.jpg"))
|
||
|
||
# 加入去灰、锐化
|
||
remove_gray_and_sharpening(jpg_path)
|
||
|
||
upload_jpg_mtl(pid, order_id, print_id)
|
||
|
||
# plt.axis('equal')
|
||
# plt.show()
|
||
|
||
# 保存blend文件
|
||
# bpy.ops.wm.save_as_mainfile(filepath=f'{workdir}{pid}_{order_id}/{pid}_qr_end.blend')
|
||
bpy.ops.wm.quit_blender()
|
||
|
||
# 删除临时文件
|
||
shutil.rmtree(os.path.join(workdir, f'{pid}_{order_id}'))
|
||
if only_one:
|
||
print(f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())} 运行{print_id}任务完成，退出程序')
|
||
break
|
||
else:
|
||
print(f'{time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())} 运行{print_id}任务完成，继续运行下一个任务')
|
||
print_id = '0'
|
||
continue
|
||
|
||
@retry(stop_max_attempt_number=10, wait_fixed=2000)
|
||
def upload_jpg_mtl(pid, order_id, print_id):
|
||
print('生成贴图完成，开始上传...')
|
||
oss_client.put_object_from_file(f'objs/print/{pid}/{pid}Tex1.{print_id}.jpg', os.path.join(workdir,f'{pid}_{order_id}', f"{pid}Tex1.jpg"))
|
||
oss_client.put_object_from_file(f'objs/print/{pid}/{pid}.mtl', os.path.join(workdir,f'{pid}_{order_id}', f"{pid}.mtl"))
|
||
# oss_client.put_object_from_file(f'objs/print/{pid}/{pid}Tex1_noqr.jpg', os.path.join(workdir,f'{pid}_{order_id}', f"{pid}Tex1_noqr.jpg"))
|
||
|
||
print('更新状态为已生成脚底板二维码')
|
||
res = requests.post(f'{upload_qr_position_url}?print_id={print_id}')
|
||
#记录日志
|
||
logging.error(f"{time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())}-结果:pid:{pid}-print_id:{print_id} {str(res.text)}")
|
||
print('更新返回状态:', f'{upload_qr_position_url}?print_id={print_id}', res.text)
|
||
|
||
if __name__ == '__main__':
|
||
low_y_limit = 25000
|
||
high_y_limit = 13000
|
||
|
||
get_qr_position_url = 'https://mp.api.suwa3d.com/api/printOrder/getFootCodePositionData'
|
||
upload_qr_position_url = 'https://mp.api.suwa3d.com/api/printOrder/updateFootCodeStatus'
|
||
get_pid_by_printid_url = 'https://mp.api.suwa3d.com/api/printOrder/getPidByPrintId'
|
||
# get_qr_position_url = 'http://172.31.1.254:8199/api/printOrder/getFootCodePositionData'
|
||
# upload_qr_position_url = 'http://172.31.1.254:8199/api/printOrder/updateFootCodeStatus'
|
||
# get_pid_by_printid_url = 'http://172.31.1.254:8199/api/printOrder/getPidByPrintId'
|
||
|
||
|
||
r = redis.Redis(host='106.14.158.208', password='kcV2000', port=6379, db=6)
|
||
# r = redis.Redis(host='172.31.1.254', password='', port=6379, db=6)
|
||
AccessKeyId = 'LTAI5tSReWm8hz7dSYxxth8f'
|
||
AccessKeySecret = '8ywTDF9upPAtvgXtLKALY2iMYHIxdS'
|
||
Endpoint = 'oss-cn-shanghai.aliyuncs.com'
|
||
Bucket = 'suwa3d-securedata'
|
||
oss_client = oss2.Bucket(oss2.Auth(AccessKeyId, AccessKeySecret), Endpoint, Bucket)
|
||
|
||
if platform.system() == 'Windows':
|
||
workdir = 'd:\\print\\'
|
||
else:
|
||
workdir = '/data/datasets/foot/'
|
||
|
||
print("Usage: blender -b -P fill_dm_code.py")
|
||
|
||
if len(sys.argv) == 5:
|
||
print_ids = sys.argv[-1]
|
||
else:
|
||
print_ids = '0'
|
||
|
||
for print_id in print_ids.split(','):
|
||
main(workdir, r, print_id)
|
||
|
||
|