diff --git a/config.py b/config.py
index d9ceefa..0a9b010 100644
--- a/config.py
+++ b/config.py
@@ -1,6 +1,8 @@
 
 # -------------------------- 开始：运行模式 -------------------------------
 
+version = "0.11.251212.1"
+
 from enum import Enum
 class run_mode(Enum):
     formal = 1
@@ -25,6 +27,7 @@ redis_config = {
 url_send_layout = 'https://mp.api.suwa3d.com/api/printTypeSettingOrder/printTypeSettingOrderSuccess'
 url_get_info_by_printIds = "https://mp.api.suwa3d.com/api/printOrder/getInfoByPrintIds?print_ids="
 url_get_oss_suffix_by_orderId = f"https://mp.api.suwa3d.com/api/order/getOssSuffixByOrderId?order_id="
+url_get_info_by_print_batch_id = f"https://mp.api.suwa3d.com/api/printOrder/getInfoByPrintBatchId?batch_id="
 
 # -------------------------- 结束：网络配置 -------------------------------
 
@@ -48,9 +51,9 @@ small_machine_size = [380, 345, 250]
 # -------------------------- 开始：测试相关 -------------------------------
 
 # local_data= {'machine_print_counts': 150, 'machine_type': 'big_machine', 'pre_batch_id': 9910032, 'print_machine_id': 14, 'print_orders': [{'counts': 1, 'layout_z': 35.62070959151145, 'model_weight': 41.862, 'order_id': 917900, 'pid': 376666, 'print_id': 126318}, {'counts': 1, 'layout_z': 31.380497732946978, 'model_weight': 35.158, 'order_id': 917810, 'pid': 376562, 'print_id': 126413}, {'counts': 1, 'layout_z': 26.136854969886777, 'model_weight': 21.403, 'order_id': 917820, 'pid': 376572, 'print_id': 126414}, {'counts': 1, 'layout_z': 37.967177899738104, 'model_weight': 30.48, 'order_id': 917922, 'pid': 376684, 'print_id': 126415}, {'counts': 1, 'layout_z': 20.368887098446734, 'model_weight': 13.097, 'order_id': 918228, 'pid': 377198, 'print_id': 126417}, {'counts': 1, 'layout_z': 21.4227336927951, 'model_weight': 15.859, 'order_id': 917576, 'pid': 376345, 'print_id': 126769}, {'counts': 1, 'layout_z': 27.539947066784066, 'model_weight': 25.185, 'order_id': 917811, 'pid': 376564, 'print_id': 126875}, {'counts': 1, 'layout_z': 31.692723822970393, 'model_weight': 32.796, 'order_id': 917821, 'pid': 376592, 'print_id': 126876}, {'counts': 1, 'layout_z': 20.20031720146163, 'model_weight': 8.664, 'order_id': 917822, 'pid': 376602, 'print_id': 126877}, {'counts': 1, 'layout_z': 22.41680629925537, 'model_weight': 15.206, 'order_id': 917827, 'pid': 376616, 'print_id': 126878}, {'counts': 1, 'layout_z': 25.443981671314514, 'model_weight': 11.965, 'order_id': 917879, 'pid': 376635, 'print_id': 126879}, {'counts': 1, 'layout_z': 31.09222672704002, 'model_weight': 20.318, 'order_id': 917902, 'pid': 376667, 'print_id': 126882}, {'counts': 1, 'layout_z': 30.3317820592175, 'model_weight': 32.964, 'order_id': 917903, 'pid': 376668, 'print_id': 126884}, {'counts': 1, 'layout_z': 28.69639626624317, 'model_weight': 27.751, 'order_id': 917904, 'pid': 376669, 'print_id': 126885}, {'counts': 1, 'layout_z': 28.043180029163203, 'model_weight': 19.866, 'order_id': 917917, 'pid': 376677, 'print_id': 126886}, {'counts': 1, 'layout_z': 28.58783468947201, 'model_weight': 25.505, 'order_id': 918196, 'pid': 377126, 'print_id': 126888}, {'counts': 1, 'layout_z': 43.55871899466554, 'model_weight': 63.512, 'order_id': 918201, 'pid': 377131, 'print_id': 126890}, {'counts': 1, 'layout_z': 32.52479624889478, 'model_weight': 22.943, 'order_id': 918203, 'pid': 377133, 'print_id': 126891}, {'counts': 1, 'layout_z': 33.21834123013511, 'model_weight': 42.163, 'order_id': 918206, 'pid': 377139, 'print_id': 126892}, {'counts': 1, 'layout_z': 27.81674335447885, 'model_weight': 15.455, 'order_id': 918207, 'pid': 377141, 'print_id': 126893}, {'counts': 1, 'layout_z': 29.78203639784899, 'model_weight': 29.696, 'order_id': 918231, 'pid': 377201, 'print_id': 126894}, {'counts': 1, 'layout_z': 23.66875736859606, 'model_weight': 13.39, 'order_id': 915637, 'pid': 373135, 'print_id': 126895}, {'counts': 1, 'layout_z': 29.00408914521088, 'model_weight': 19.553, 'order_id': 918246, 'pid': 377209, 'print_id': 126897}, {'counts': 1, 'layout_z': 24.44397251338635, 'model_weight': 15.424, 'order_id': 918325, 'pid': 376974, 'print_id': 126899}, {'counts': 1, 'layout_z': 31.755406379699707, 'model_weight': 31.131, 'order_id': 918492, 'pid': 377584, 'print_id': 126900}, {'counts': 1, 'layout_z': 38.03699946264237, 'model_weight': 47.412, 'order_id': 918493, 'pid': 377587, 'print_id': 126901}, {'counts': 1, 'layout_z': 43.52919799223749, 'model_weight': 37.842, 'order_id': 918494, 'pid': 377589, 'print_id': 126902}, {'counts': 1, 'layout_z': 25.906302369108843, 'model_weight': 18.64, 'order_id': 918495, 'pid': 377590, 'print_id': 126903}, {'counts': 1, 'layout_z': 36.02611978829816, 'model_weight': 43.814, 'order_id': 918496, 'pid': 377591, 'print_id': 126904}, {'counts': 1, 'layout_z': 26.020689766262052, 'model_weight': 18.513, 'order_id': 918497, 'pid': 377594, 'print_id': 126905}, {'counts': 1, 'layout_z': 23.988078117370605, 'model_weight': 15.753, 'order_id': 918498, 'pid': 377596, 'print_id': 126906}, {'counts': 1, 'layout_z': 27.457814063914604, 'model_weight': 23.507, 'order_id': 918500, 'pid': 377601, 'print_id': 126908}, {'counts': 1, 'layout_z': 29.306090320672993, 'model_weight': 25.043, 'order_id': 918501, 'pid': 377605, 'print_id': 126909}, {'counts': 1, 'layout_z': 29.070231478924583, 'model_weight': 25.598, 'order_id': 918504, 'pid': 377606, 'print_id': 126910}, {'counts': 1, 'layout_z': 24.314504768436095, 'model_weight': 18.68, 'order_id': 918555, 'pid': 377684, 'print_id': 126911}, {'counts': 1, 'layout_z': 37.52979171030315, 'model_weight': 53.541, 'order_id': 918558, 'pid': 377689, 'print_id': 126913}, {'counts': 1, 'layout_z': 26.530791960490333, 'model_weight': 15.082, 'order_id': 918560, 'pid': 377702, 'print_id': 126915}, {'counts': 1, 'layout_z': 23.604568481445312, 'model_weight': 21.614, 'order_id': 918583, 'pid': 377748, 'print_id': 126917}, {'counts': 1, 'layout_z': 27.865868478825355, 'model_weight': 22.6, 'order_id': 918636, 'pid': 377819, 'print_id': 126919}, {'counts': 1, 'layout_z': 30.786012113461286, 'model_weight': 25.699, 'order_id': 919105, 'pid': 378621, 'print_id': 126926}, {'counts': 1, 'layout_z': 27.39871813917613, 'model_weight': 20.061, 'order_id': 919106, 'pid': 378638, 'print_id': 126927}, {'counts': 1, 'layout_z': 37.645312213517265, 'model_weight': 42.591, 'order_id': 919018, 'pid': 377979, 'print_id': 126929}, {'counts': 1, 'layout_z': 53.26858516168712, 'model_weight': 130.558, 'order_id': 919110, 'pid': 378650, 'print_id': 126930}, {'counts': 1, 'layout_z': 27.335996763557635, 'model_weight': 19.724, 'order_id': 919024, 'pid': 378409, 'print_id': 126935}, {'counts': 1, 'layout_z': 23.94061705626402, 'model_weight': 15.026, 'order_id': 917479, 'pid': 376087, 'print_id': 126940}, {'counts': 1, 'layout_z': 29.543430158218627, 'model_weight': 19.191, 'order_id': 919012, 'pid': 378375, 'print_id': 126943}, {'counts': 1, 'layout_z': 27.454958866692724, 'model_weight': 22.776, 'order_id': 918499, 'pid': 377599, 'print_id': 126946}, {'counts': 1, 'layout_z': 29.367137022488468, 'model_weight': 22.455, 'order_id': 918559, 'pid': 377700, 'print_id': 126947}, {'counts': 1, 'layout_z': 29.209802512215997, 'model_weight': 22.524, 'order_id': 918569, 'pid': 377740, 'print_id': 126948}, {'counts': 1, 'layout_z': 25.396360323579223, 'model_weight': 20.442, 'order_id': 919228, 'pid': 378700, 'print_id': 126949}, {'counts': 1, 'layout_z': 28.232575120695085, 'model_weight': 24.391, 'order_id': 919229, 'pid': 378701, 'print_id': 126950}, {'counts': 1, 'layout_z': 31.82000351720909, 'model_weight': 35.189, 'order_id': 918580, 'pid': 377743, 'print_id': 126951}, {'counts': 1, 'layout_z': 18.000296592712402, 'model_weight': 5.264, 'order_id': 919230, 'pid': 378702, 'print_id': 126952}, {'counts': 1, 'layout_z': 32.6660716900792, 'model_weight': 21.182, 'order_id': 918581, 'pid': 377744, 'print_id': 126953}, {'counts': 1, 'layout_z': 20.317776580664418, 'model_weight': 6.793, 'order_id': 919231, 'pid': 378703, 'print_id': 126954}, {'counts': 1, 'layout_z': 23.08764836740975, 'model_weight': 12.265, 'order_id': 918582, 'pid': 377745, 'print_id': 126955}, {'counts': 1, 'layout_z': 22.843233481777308, 'model_weight': 12.229, 'order_id': 918783, 'pid': 378073, 'print_id': 126956}, {'counts': 1, 'layout_z': 17.441239242068544, 'model_weight': 4.888, 'order_id': 919233, 'pid': 378705, 'print_id': 126957}, {'counts': 1, 'layout_z': 18.11011046132721, 'model_weight': 5.835, 'order_id': 919234, 'pid': 378706, 'print_id': 126958}, {'counts': 1, 'layout_z': 16.299313366344762, 'model_weight': 4.977, 'order_id': 919232, 'pid': 378704, 'print_id': 126959}, {'counts': 1, 'layout_z': 16.977858537144982, 'model_weight': 4.423, 'order_id': 919235, 'pid': 378707, 'print_id': 126960}, {'counts': 1, 'layout_z': 19.66670311054518, 'model_weight': 6.836, 'order_id': 919236, 'pid': 378708, 'print_id': 126962}, {'counts': 1, 'layout_z': 16.450413533497088, 'model_weight': 4.404, 'order_id': 919237, 'pid': 378709, 'print_id': 126963}, {'counts': 1, 'layout_z': 19.12714231472859, 'model_weight': 6.788, 'order_id': 919238, 'pid': 378711, 'print_id': 126965}, {'counts': 1, 'layout_z': 15.662716096748905, 'model_weight': 5.399, 'order_id': 919239, 'pid': 378712, 'print_id': 126966}, {'counts': 1, 'layout_z': 17.984565068326873, 'model_weight': 5.224, 'order_id': 919240, 'pid': 378713, 'print_id': 126968}, {'counts': 1, 'layout_z': 18.779169416653758, 'model_weight': 6.097, 'order_id': 919243, 'pid': 378715, 'print_id': 126971}, {'counts': 1, 'layout_z': 17.88619578087645, 'model_weight': 6.155, 'order_id': 919244, 'pid': 378716, 'print_id': 126972}, {'counts': 1, 'layout_z': 18.061075125597053, 'model_weight': 6.012, 'order_id': 919245, 'pid': 378717, 'print_id': 126973}, {'counts': 1, 'layout_z': 18.02680370824573, 'model_weight': 5.248, 'order_id': 919246, 'pid': 378718, 'print_id': 126974}, {'counts': 1, 'layout_z': 18.23313922758454, 'model_weight': 4.889, 'order_id': 919247, 'pid': 378719, 'print_id': 126975}, {'counts': 1, 'layout_z': 15.10249208974721, 'model_weight': 4.305, 'order_id': 919248, 'pid': 378720, 'print_id': 126976}, {'counts': 1, 'layout_z': 26.393060472696845, 'model_weight': 18.787, 'order_id': 919249, 'pid': 378721, 'print_id': 126978}, {'counts': 1, 'layout_z': 30.27226940032898, 'model_weight': 20.279, 'order_id': 919250, 'pid': 378722, 'print_id': 126979}, {'counts': 1, 'layout_z': 33.275894165039055, 'model_weight': 30.53, 'order_id': 919026, 'pid': 378415, 'print_id': 126980}, {'counts': 1, 'layout_z': 19.061190510799264, 'model_weight': 7.443, 'order_id': 919251, 'pid': 378723, 'print_id': 126981}, {'counts': 1, 'layout_z': 22.21409211773961, 'model_weight': 7.147, 'order_id': 919252, 'pid': 378724, 'print_id': 126982}, {'counts': 1, 'layout_z': 31.450466048829572, 'model_weight': 30.067, 'order_id': 919030, 'pid': 378420, 'print_id': 126983}, {'counts': 1, 'layout_z': 16.95446233116205, 'model_weight': 5.067, 'order_id': 919253, 'pid': 378725, 'print_id': 126984}, {'counts': 1, 'layout_z': 26.16507487130793, 'model_weight': 18.558, 'order_id': 919031, 'pid': 378425, 'print_id': 126985}, {'counts': 1, 'layout_z': 16.012466453733403, 'model_weight': 6.216, 'order_id': 919255, 'pid': 378727, 'print_id': 126987}, {'counts': 1, 'layout_z': 20.30786979564451, 'model_weight': 7.149, 'order_id': 919256, 'pid': 378728, 'print_id': 126989}, {'counts': 1, 'layout_z': 21.65708123870792, 'model_weight': 8.508, 'order_id': 919257, 'pid': 378729, 'print_id': 126990}, {'counts': 1, 'layout_z': 17.955288402689746, 'model_weight': 6.014, 'order_id': 919258, 'pid': 378730, 'print_id': 126991}, {'counts': 1, 'layout_z': 19.3577859181912, 'model_weight': 7.269, 'order_id': 919259, 'pid': 378731, 'print_id': 126992}, {'counts': 1, 'layout_z': 16.81846154205583, 'model_weight': 4.525, 'order_id': 919260, 'pid': 378732, 'print_id': 126993}, {'counts': 1, 'layout_z': 27.407528874290133, 'model_weight': 20.443, 'order_id': 919261, 'pid': 378733, 'print_id': 126994}, {'counts': 1, 'layout_z': 34.374910104166425, 'model_weight': 24.786, 'order_id': 919263, 'pid': 378737, 'print_id': 126995}, {'counts': 1, 'layout_z': 22.392321514992663, 'model_weight': 13.752, 'order_id': 919264, 'pid': 378738, 'print_id': 126996}, {'counts': 1, 'layout_z': 18.011880302127423, 'model_weight': 5.473, 'order_id': 919265, 'pid': 378739, 'print_id': 126997}, {'counts': 1, 'layout_z': 28.383317524486593, 'model_weight': 21.997, 'order_id': 919266, 'pid': 378743, 'print_id': 126998}, {'counts': 1, 'layout_z': 23.672918816217553, 'model_weight': 16.46, 'order_id': 917480, 'pid': 376067, 'print_id': 126999}, {'counts': 1, 'layout_z': 16.479959151650828, 'model_weight': 5.821, 'order_id': 919267, 'pid': 378744, 'print_id': 127000}, {'counts': 1, 'layout_z': 35.155273295967994, 'model_weight': 48.551, 'order_id': 919268, 'pid': 378745, 'print_id': 127001}, {'counts': 1, 'layout_z': 25.231643428560584, 'model_weight': 19.358, 'order_id': 917478, 'pid': 376098, 'print_id': 127002}, {'counts': 1, 'layout_z': 16.688496289759275, 'model_weight': 5.743, 'order_id': 919269, 'pid': 378746, 'print_id': 127003}, {'counts': 1, 'layout_z': 27.167236561321484, 'model_weight': 21.521, 'order_id': 919270, 'pid': 378747, 'print_id': 127004}, {'counts': 1, 'layout_z': 25.463308095650035, 'model_weight': 10.912, 'order_id': 919271, 'pid': 378748, 'print_id': 127005}, {'counts': 1, 'layout_z': 25.206470863711544, 'model_weight': 10.581, 'order_id': 919272, 'pid': 378749, 'print_id': 127007}, {'counts': 1, 'layout_z': 26.25579441073758, 'model_weight': 13.336, 'order_id': 919273, 'pid': 378750, 'print_id': 127008}, {'counts': 1, 'layout_z': 22.231088289345216, 'model_weight': 12.438, 'order_id': 919014, 'pid': 378382, 'print_id': 127009}, {'counts': 1, 'layout_z': 26.20472244790368, 'model_weight': 14.247, 'order_id': 919274, 'pid': 378751, 'print_id': 127010}, {'counts': 1, 'layout_z': 25.164680222473894, 'model_weight': 15.369, 'order_id': 918502, 'pid': 377099, 'print_id': 127015}, {'counts': 1, 'layout_z': 24.15820278087022, 'model_weight': 16.648, 'order_id': 919219, 'pid': 378697, 'print_id': 127017}, {'counts': 1, 'layout_z': 16.35217992064665, 'model_weight': 5.306, 'order_id': 919182, 'pid': 378518, 'print_id': 127018}, {'counts': 1, 'layout_z': 21.25218355838687, 'model_weight': 10.043, 'order_id': 918230, 'pid': 377200, 'print_id': 127019}, {'counts': 1, 'layout_z': 33.729734231090276, 'model_weight': 49.911, 'order_id': 919276, 'pid': 378776, 'print_id': 127020}, {'counts': 1, 'layout_z': 24.560107711202825, 'model_weight': 8.349, 'order_id': 919282, 'pid': 378798, 'print_id': 127027}, {'counts': 1, 'layout_z': 21.12561534577449, 'model_weight': 7.557, 'order_id': 919287, 'pid': 378803, 'print_id': 127031}, {'counts': 1, 'layout_z': 25.091119425246845, 'model_weight': 14.908, 'order_id': 919292, 'pid': 378808, 'print_id': 127037}, {'counts': 1, 'layout_z': 26.77140074489941, 'model_weight': 21.134, 'order_id': 919293, 'pid': 378809, 'print_id': 127038}, {'counts': 1, 'layout_z': 27.517811122519632, 'model_weight': 20.529, 'order_id': 919294, 'pid': 378810, 'print_id': 127040}, {'counts': 1, 'layout_z': 30.62898230748005, 'model_weight': 22.053, 'order_id': 918507, 'pid': 377607, 'print_id': 127041}, {'counts': 1, 'layout_z': 27.056545744705435, 'model_weight': 20.734, 'order_id': 919295, 'pid': 378811, 'print_id': 127042}, {'counts': 1, 'layout_z': 23.059078062109105, 'model_weight': 13.642, 'order_id': 918508, 'pid': 377610, 'print_id': 127044}, {'counts': 1, 'layout_z': 24.373135283888665, 'model_weight': 18.763, 'order_id': 919297, 'pid': 378814, 'print_id': 127045}, {'counts': 1, 'layout_z': 29.93312254092476, 'model_weight': 28.184, 'order_id': 918556, 'pid': 377685, 'print_id': 127046}, {'counts': 1, 'layout_z': 35.433726822945225, 'model_weight': 46.28, 'order_id': 919298, 'pid': 378815, 'print_id': 127047}, {'counts': 1, 'layout_z': 32.148966009725754, 'model_weight': 43.827, 'order_id': 919299, 'pid': 378816, 'print_id': 127048}, {'counts': 1, 'layout_z': 24.873977270254855, 'model_weight': 17.694, 'order_id': 919300, 'pid': 378817, 'print_id': 127049}, {'counts': 1, 'layout_z': 28.89906702733768, 'model_weight': 19.09, 'order_id': 918568, 'pid': 377739, 'print_id': 127050}, {'counts': 1, 'layout_z': 29.072691539058013, 'model_weight': 24.701, 'order_id': 919301, 'pid': 378818, 'print_id': 127051}, {'counts': 1, 'layout_z': 22.799459457397457, 'model_weight': 17.986, 'order_id': 919302, 'pid': 378819, 'print_id': 127052}, {'counts': 1, 'layout_z': 28.30774288615256, 'model_weight': 23.62, 'order_id': 919303, 'pid': 378820, 'print_id': 127054}, {'counts': 1, 'layout_z': 27.685387987537027, 'model_weight': 18.804, 'order_id': 919304, 'pid': 378821, 'print_id': 127055}, {'counts': 1, 'layout_z': 21.501308067252822, 'model_weight': 7.512, 'order_id': 919305, 'pid': 378822, 'print_id': 127056}, {'counts': 1, 'layout_z': 31.91424955213119, 'model_weight': 37.428, 'order_id': 919307, 'pid': 378823, 'print_id': 127057}, {'counts': 1, 'layout_z': 32.039728096944266, 'model_weight': 35.473, 'order_id': 919308, 'pid': 378824, 'print_id': 127058}, {'counts': 1, 'layout_z': 33.27248765777313, 'model_weight': 37.264, 'order_id': 919309, 'pid': 378825, 'print_id': 127059}, {'counts': 1, 'layout_z': 31.01150813726163, 'model_weight': 27.421, 'order_id': 919310, 'pid': 378826, 'print_id': 127060}, {'counts': 1, 'layout_z': 25.02092682146464, 'model_weight': 16.694, 'order_id': 919311, 'pid': 378827, 'print_id': 127061}, {'counts': 1, 'layout_z': 27.649195956325578, 'model_weight': 20.131, 'order_id': 919314, 'pid': 378831, 'print_id': 127062}, {'counts': 1, 'layout_z': 29.323484806820524, 'model_weight': 23.913, 'order_id': 919313, 'pid': 378830, 'print_id': 127063}, {'counts': 1, 'layout_z': 29.93491564175814, 'model_weight': 27.02, 'order_id': 919312, 'pid': 378829, 'print_id': 127064}, {'counts': 1, 'layout_z': 29.220408560439278, 'model_weight': 25.891, 'order_id': 919316, 'pid': 378834, 'print_id': 127066}, {'counts': 1, 'layout_z': 27.086421547538176, 'model_weight': 21.186, 'order_id': 919317, 'pid': 378835, 'print_id': 127067}, {'counts': 1, 'layout_z': 29.687568424918922, 'model_weight': 22.681, 'order_id': 919318, 'pid': 378836, 'print_id': 127068}, {'counts': 1, 'layout_z': 30.30524230403575, 'model_weight': 26.048, 'order_id': 919319, 'pid': 378837, 'print_id': 127069}, {'counts': 1, 'layout_z': 24.082729373309707, 'model_weight': 18.03, 'order_id': 919322, 'pid': 378840, 'print_id': 127072}, {'counts': 1, 'layout_z': 27.8159610614131, 'model_weight': 21.29, 'order_id': 919321, 'pid': 378839, 'print_id': 127073}, {'counts': 1, 'layout_z': 28.93995122935326, 'model_weight': 21.318, 'order_id': 919326, 'pid': 378844, 'print_id': 127074}, {'counts': 1, 'layout_z': 27.58645357098898, 'model_weight': 23.726, 'order_id': 919324, 'pid': 378842, 'print_id': 127076}, {'counts': 1, 'layout_z': 26.337441702233544, 'model_weight': 23.781, 'order_id': 919329, 'pid': 378847, 'print_id': 127077}, {'counts': 1, 'layout_z': 25.032097288221692, 'model_weight': 17.614, 'order_id': 919328, 'pid': 378846, 'print_id': 127078}, {'counts': 1, 'layout_z': 27.0008910375328, 'model_weight': 20.06, 'order_id': 919327, 'pid': 378845, 'print_id': 127079}, {'counts': 1, 'layout_z': 28.573475817385898, 'model_weight': 22.823, 'order_id': 919334, 'pid': 378852, 'print_id': 127081}, {'counts': 1, 'layout_z': 23.589348437207477, 'model_weight': 19.486, 'order_id': 919335, 'pid': 378853, 'print_id': 127082}, {'counts': 1, 'layout_z': 28.29603645275283, 'model_weight': 20.464, 'order_id': 919330, 'pid': 378848, 'print_id': 127083}, {'counts': 1, 'layout_z': 36.094532611977854, 'model_weight': 19.122, 'order_id': 919333, 'pid': 378851, 'print_id': 127084}, {'counts': 1, 'layout_z': 26.209464742348054, 'model_weight': 20.434, 'order_id': 919331, 'pid': 378849, 'print_id': 127085}]}
-# local_data= {"machine_print_counts":50, 'machine_type': 'small_machine',"pre_batch_id":991112,"print_machine_id":22,"print_orders":[{"counts":1,"layout_z":3.543965775898459,"model_weight":12.833,"order_id":857420,"pid":268473,"print_id":85240},{"counts":1,"layout_z":7.798861189952786,"model_weight":13.784,"order_id":875986,"pid":305425,"print_id":88136}]}
+local_data= {"machine_print_counts":50, 'machine_type': 'small_machine',"pre_batch_id":991112,"print_machine_id":22,"print_orders":[{"counts":1,"layout_z":3.543965775898459,"model_weight":12.833,"order_id":857420,"pid":268473,"print_id":85240},{"counts":1,"layout_z":7.798861189952786,"model_weight":13.784,"order_id":875986,"pid":305425,"print_id":88136}]}
 # local_data= {'machine_print_counts': 130, 'machine_type': 'big_machine', 'pre_batch_id': 9910188, 'print_machine_id': 15, 'print_orders': [{'counts': 1, 'layout_z': 32.65071311811036, 'model_weight': 68.084, 'order_id': 926400, 'pid': 389256, 'print_id': 134168}, {'counts': 1, 'layout_z': 31.780598561603746, 'model_weight': 25.511, 'order_id': 926573, 'pid': 389465, 'print_id': 134170}, {'counts': 1, 'layout_z': 5.202356934547428, 'model_weight': 11.705, 'order_id': 925909, 'pid': 388682, 'print_id': 134178}, {'counts': 1, 'layout_z': 5.1447470188140905, 'model_weight': 12.186, 'order_id': 925910, 'pid': 388683, 'print_id': 134179}, {'counts': 1, 'layout_z': 5.013986945152283, 'model_weight': 11.364, 'order_id': 925932, 'pid': 388707, 'print_id': 134180}, {'counts': 1, 'layout_z': 5.020000934600831, 'model_weight': 11.396, 'order_id': 926770, 'pid': 389842, 'print_id': 134183}, {'counts': 1, 'layout_z': 40.05588230441501, 'model_weight': 60.578, 'order_id': 926776, 'pid': 389895, 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'order_id': 927208, 'pid': 390478, 'print_id': 134348}, {'counts': 1, 'layout_z': 20.210533386684535, 'model_weight': 7.052, 'order_id': 927209, 'pid': 390479, 'print_id': 134349}, {'counts': 1, 'layout_z': 25.121042400893273, 'model_weight': 19.767, 'order_id': 926136, 'pid': 388923, 'print_id': 134350}, {'counts': 1, 'layout_z': 22.556339860084357, 'model_weight': 11.815, 'order_id': 927211, 'pid': 390481, 'print_id': 134351}, {'counts': 1, 'layout_z': 18.46208941910043, 'model_weight': 5.893, 'order_id': 927210, 'pid': 390480, 'print_id': 134352}, {'counts': 1, 'layout_z': 32.68489185465737, 'model_weight': 45.948, 'order_id': 927212, 'pid': 390482, 'print_id': 134353}, {'counts': 1, 'layout_z': 24.92353755904854, 'model_weight': 17.616, 'order_id': 927214, 'pid': 390483, 'print_id': 134354}, {'counts': 1, 'layout_z': 21.95895233294398, 'model_weight': 7.069, 'order_id': 927215, 'pid': 390484, 'print_id': 134355}, {'counts': 1, 'layout_z': 20.092923892436325, 'model_weight': 7.836, 'order_id': 927216, 'pid': 390485, 'print_id': 134356}, {'counts': 1, 'layout_z': 26.52895418595368, 'model_weight': 19.424, 'order_id': 927217, 'pid': 390486, 'print_id': 134357}, {'counts': 1, 'layout_z': 30.77656556343579, 'model_weight': 24.309, 'order_id': 927218, 'pid': 390487, 'print_id': 134358}, {'counts': 1, 'layout_z': 35.55027093112967, 'model_weight': 79.912, 'order_id': 926144, 'pid': 388930, 'print_id': 134359}, {'counts': 1, 'layout_z': 34.666106095305544, 'model_weight': 45.102, 'order_id': 927219, 'pid': 390488, 'print_id': 134360}, {'counts': 1, 'layout_z': 19.70823874073735, 'model_weight': 7.716, 'order_id': 927220, 'pid': 390489, 'print_id': 134361}, {'counts': 1, 'layout_z': 20.494914757611284, 'model_weight': 23.484, 'order_id': 926167, 'pid': 388953, 'print_id': 134362}, {'counts': 1, 'layout_z': 23.325873325059348, 'model_weight': 21.341, 'order_id': 926172, 'pid': 388958, 'print_id': 134363}, {'counts': 1, 'layout_z': 31.17877079215529, 'model_weight': 34.749, 'order_id': 927230, 'pid': 390496, 'print_id': 134364}, {'counts': 1, 'layout_z': 35.113171234632325, 'model_weight': 52.7, 'order_id': 927229, 'pid': 390495, 'print_id': 134365}, {'counts': 1, 'layout_z': 33.07103017293801, 'model_weight': 22.034, 'order_id': 927232, 'pid': 390498, 'print_id': 134366}, {'counts': 1, 'layout_z': 37.581496313110925, 'model_weight': 52.109, 'order_id': 927231, 'pid': 390497, 'print_id': 134367}, {'counts': 1, 'layout_z': 17.542512801134045, 'model_weight': 6.737, 'order_id': 927233, 'pid': 390499, 'print_id': 134368}, {'counts': 1, 'layout_z': 32.368560440954866, 'model_weight': 32.587, 'order_id': 927234, 'pid': 390500, 'print_id': 134369}, {'counts': 1, 'layout_z': 33.806879483311434, 'model_weight': 41.356, 'order_id': 927236, 'pid': 390502, 'print_id': 134370}, {'counts': 1, 'layout_z': 19.460627187140275, 'model_weight': 6.741, 'order_id': 927237, 'pid': 390503, 'print_id': 134371}, {'counts': 1, 'layout_z': 27.412082567923058, 'model_weight': 21.154, 'order_id': 927239, 'pid': 390505, 'print_id': 134372}, {'counts': 1, 'layout_z': 18.139268993783688, 'model_weight': 6.906, 'order_id': 927238, 'pid': 390504, 'print_id': 134373}, {'counts': 1, 'layout_z': 36.699612270516404, 'model_weight': 51.275, 'order_id': 927235, 'pid': 390501, 'print_id': 134374}, {'counts': 1, 'layout_z': 29.11257547114117, 'model_weight': 25.871, 'order_id': 927240, 'pid': 390506, 'print_id': 134375}]}
-local_data= {'machine_print_counts': 60, 'machine_type': 'small_machine', 'pre_batch_id': 10284, 'print_machine_id': 1, 'print_orders': [{'counts': 1, 'layout_z': 6.981930971145635, 'model_weight': 26.776, 'order_id': 929174, 'pid': 393697, 'print_id': 138265}, {'counts': 1, 'layout_z': 4.955404043197634, 'model_weight': 9.22, 'order_id': 931997, 'pid': 397013, 'print_id': 138846}, {'counts': 1, 'layout_z': 4.771067023277285, 'model_weight': 11.786, 'order_id': 932000, 'pid': 397016, 'print_id': 138851}, {'counts': 1, 'layout_z': 5.249161005020142, 'model_weight': 10.024, 'order_id': 932003, 'pid': 397019, 'print_id': 138854}, {'counts': 1, 'layout_z': 5.251940011978151, 'model_weight': 10.104, 'order_id': 932005, 'pid': 397021, 'print_id': 138856}, {'counts': 1, 'layout_z': 5.263678073883059, 'model_weight': 10.688, 'order_id': 932009, 'pid': 397025, 'print_id': 138875}, {'counts': 1, 'layout_z': 23.813366889953613, 'model_weight': 24.641, 'order_id': 929102, 'pid': 393961, 'print_id': 139071}, {'counts': 1, 'layout_z': 4.554790019989014, 'model_weight': 11.507, 'order_id': 933586, 'pid': 399522, 'print_id': 140121}, {'counts': 1, 'layout_z': 4.795650005340576, 'model_weight': 11.042, 'order_id': 933568, 'pid': 399331, 'print_id': 140150}, {'counts': 1, 'layout_z': 18.085672736889748, 'model_weight': 7.277, 'order_id': 933876, 'pid': 399901, 'print_id': 140261}, {'counts': 1, 'layout_z': 19.534520236131655, 'model_weight': 6.937, 'order_id': 933878, 'pid': 399903, 'print_id': 140264}, {'counts': 1, 'layout_z': 19.559980709635155, 'model_weight': 7.79, 'order_id': 933877, 'pid': 399902, 'print_id': 140265}, {'counts': 1, 'layout_z': 16.488399505615234, 'model_weight': 5.349, 'order_id': 933882, 'pid': 399907, 'print_id': 140271}, {'counts': 1, 'layout_z': 18.02717763893993, 'model_weight': 5.892, 'order_id': 933885, 'pid': 399910, 'print_id': 140277}, {'counts': 1, 'layout_z': 26.876644549545638, 'model_weight': 21.486, 'order_id': 933886, 'pid': 399911, 'print_id': 140278}, {'counts': 1, 'layout_z': 28.074640440717047, 'model_weight': 16.17, 'order_id': 933887, 'pid': 399912, 'print_id': 140280}, {'counts': 1, 'layout_z': 27.306154248118705, 'model_weight': 20.977, 'order_id': 933889, 'pid': 399927, 'print_id': 140281}, {'counts': 1, 'layout_z': 26.094746051465723, 'model_weight': 34.197, 'order_id': 933888, 'pid': 399926, 'print_id': 140282}, {'counts': 1, 'layout_z': 15.87796963527322, 'model_weight': 4.735, 'order_id': 933892, 'pid': 399930, 'print_id': 140287}, {'counts': 1, 'layout_z': 18.191209446277444, 'model_weight': 5.246, 'order_id': 933893, 'pid': 399931, 'print_id': 140288}, {'counts': 1, 'layout_z': 17.777126572389776, 'model_weight': 6.334, 'order_id': 933894, 'pid': 399932, 'print_id': 140289}, {'counts': 1, 'layout_z': 17.58385879418167, 'model_weight': 5.8, 'order_id': 933895, 'pid': 399933, 'print_id': 140290}, {'counts': 1, 'layout_z': 18.593739251800994, 'model_weight': 6.955, 'order_id': 933897, 'pid': 399935, 'print_id': 140293}, {'counts': 1, 'layout_z': 14.231568581173965, 'model_weight': 3.705, 'order_id': 933898, 'pid': 399936, 'print_id': 140294}, {'counts': 1, 'layout_z': 13.998784146949038, 'model_weight': 3.533, 'order_id': 933899, 'pid': 399937, 'print_id': 140295}, {'counts': 1, 'layout_z': 15.9964307861582, 'model_weight': 4.301, 'order_id': 933901, 'pid': 399939, 'print_id': 140297}, {'counts': 1, 'layout_z': 16.18931739014667, 'model_weight': 5.019, 'order_id': 933903, 'pid': 399941, 'print_id': 140299}, {'counts': 1, 'layout_z': 24.79611153168641, 'model_weight': 20.601, 'order_id': 933905, 'pid': 399943, 'print_id': 140301}, {'counts': 1, 'layout_z': 24.306803898330127, 'model_weight': 16.784, 'order_id': 933906, 'pid': 399944, 'print_id': 140302}, {'counts': 1, 'layout_z': 29.3158714015686, 'model_weight': 19.351, 'order_id': 933907, 'pid': 399945, 'print_id': 140303}, {'counts': 1, 'layout_z': 17.005620048049607, 'model_weight': 5.169, 'order_id': 933910, 'pid': 399948, 'print_id': 140305}, {'counts': 1, 'layout_z': 16.464274211211865, 'model_weight': 4.866, 'order_id': 933909, 'pid': 399947, 'print_id': 140306}, {'counts': 1, 'layout_z': 23.198866489386088, 'model_weight': 10.524, 'order_id': 933911, 'pid': 399949, 'print_id': 140307}, {'counts': 1, 'layout_z': 26.516445616407367, 'model_weight': 23.957, 'order_id': 933912, 'pid': 399950, 'print_id': 140308}, {'counts': 1, 'layout_z': 17.937848519147412, 'model_weight': 5.282, 'order_id': 933914, 'pid': 399952, 'print_id': 140310}, {'counts': 1, 'layout_z': 26.754205819816015, 'model_weight': 20.607, 'order_id': 933921, 'pid': 399957, 'print_id': 140315}, {'counts': 1, 'layout_z': 20.002697843362704, 'model_weight': 7.63, 'order_id': 933924, 'pid': 399960, 'print_id': 140318}, {'counts': 1, 'layout_z': 30.231639651233593, 'model_weight': 24.508, 'order_id': 933925, 'pid': 399961, 'print_id': 140319}, {'counts': 1, 'layout_z': 16.061075531610975, 'model_weight': 4.195, 'order_id': 933928, 'pid': 399964, 'print_id': 140320}, {'counts': 1, 'layout_z': 15.115618198253117, 'model_weight': 3.217, 'order_id': 933929, 'pid': 399965, 'print_id': 140323}, {'counts': 1, 'layout_z': 20.147708222788964, 'model_weight': 7.246, 'order_id': 933960, 'pid': 400001, 'print_id': 140325}, {'counts': 1, 'layout_z': 16.839157818561507, 'model_weight': 5.147, 'order_id': 933962, 'pid': 400003, 'print_id': 140327}, {'counts': 1, 'layout_z': 18.260445870716055, 'model_weight': 5.598, 'order_id': 933963, 'pid': 400004, 'print_id': 140328}, {'counts': 1, 'layout_z': 15.999999046325684, 'model_weight': 4.16, 'order_id': 933964, 'pid': 400005, 'print_id': 140329}, {'counts': 1, 'layout_z': 23.418245000534494, 'model_weight': 15.579, 'order_id': 933967, 'pid': 400008, 'print_id': 140333}, {'counts': 1, 'layout_z': 28.939651438044436, 'model_weight': 31.598, 'order_id': 933970, 'pid': 400024, 'print_id': 140335}, {'counts': 1, 'layout_z': 14.9528131844746, 'model_weight': 3.438, 'order_id': 933972, 'pid': 400026, 'print_id': 140337}, {'counts': 1, 'layout_z': 14.919241260134326, 'model_weight': 4.573, 'order_id': 933974, 'pid': 400028, 'print_id': 140340}, {'counts': 1, 'layout_z': 17.26018167267985, 'model_weight': 5.882, 'order_id': 933975, 'pid': 400029, 'print_id': 140342}, {'counts': 1, 'layout_z': 28.157231966147624, 'model_weight': 25.408, 'order_id': 933976, 'pid': 400030, 'print_id': 140343}, {'counts': 1, 'layout_z': 28.3214832027494, 'model_weight': 21.904, 'order_id': 933977, 'pid': 400031, 'print_id': 140344}, {'counts': 1, 'layout_z': 23.17201737455146, 'model_weight': 14.336, 'order_id': 933979, 'pid': 400033, 'print_id': 140346}, {'counts': 1, 'layout_z': 4.562267065048218, 'model_weight': 12.343, 'order_id': 933577, 'pid': 399494, 'print_id': 140676}, {'counts': 1, 'layout_z': 27.36789647731373, 'model_weight': 28.917, 'order_id': 932799, 'pid': 397657, 'print_id': 141912}, {'counts': 1, 'layout_z': 6.184627175331121, 'model_weight': 23.683, 'order_id': 932029, 'pid': 397140, 'print_id': 141954}, {'counts': 1, 'layout_z': 28.632703110041838, 'model_weight': 29.224, 'order_id': 933097, 'pid': 398980, 'print_id': 142034}, {'counts': 1, 'layout_z': 29.13069982014371, 'model_weight': 38.882, 'order_id': 926254, 'pid': 389047, 'print_id': 142052}, {'counts': 1, 'layout_z': 26.624711034938723, 'model_weight': 20.721, 'order_id': 933136, 'pid': 398998, 'print_id': 142056}, {'counts': 1, 'layout_z': 23.73959009314062, 'model_weight': 30.124, 'order_id': 928988, 'pid': 393851, 'print_id': 142057}, {'counts': 1, 'layout_z': 29.556987644497696, 'model_weight': 23.687, 'order_id': 933093, 'pid': 398975, 'print_id': 142059}]}
+# local_data= {'machine_print_counts': 60, 'machine_type': 'small_machine', 'pre_batch_id': 9910284, 'print_machine_id': 1, 'print_orders': [{'counts': 1, 'layout_z': 6.981930971145635, 'model_weight': 26.776, 'order_id': 929174, 'pid': 393697, 'print_id': 138265}, {'counts': 1, 'layout_z': 4.955404043197634, 'model_weight': 9.22, 'order_id': 931997, 'pid': 397013, 'print_id': 138846}, {'counts': 1, 'layout_z': 4.771067023277285, 'model_weight': 11.786, 'order_id': 932000, 'pid': 397016, 'print_id': 138851}, {'counts': 1, 'layout_z': 5.249161005020142, 'model_weight': 10.024, 'order_id': 932003, 'pid': 397019, 'print_id': 138854}, {'counts': 1, 'layout_z': 5.251940011978151, 'model_weight': 10.104, 'order_id': 932005, 'pid': 397021, 'print_id': 138856}, {'counts': 1, 'layout_z': 5.263678073883059, 'model_weight': 10.688, 'order_id': 932009, 'pid': 397025, 'print_id': 138875}, {'counts': 1, 'layout_z': 23.813366889953613, 'model_weight': 24.641, 'order_id': 929102, 'pid': 393961, 'print_id': 139071}, {'counts': 1, 'layout_z': 4.554790019989014, 'model_weight': 11.507, 'order_id': 933586, 'pid': 399522, 'print_id': 140121}, {'counts': 1, 'layout_z': 4.795650005340576, 'model_weight': 11.042, 'order_id': 933568, 'pid': 399331, 'print_id': 140150}, {'counts': 1, 'layout_z': 18.085672736889748, 'model_weight': 7.277, 'order_id': 933876, 'pid': 399901, 'print_id': 140261}, {'counts': 1, 'layout_z': 19.534520236131655, 'model_weight': 6.937, 'order_id': 933878, 'pid': 399903, 'print_id': 140264}, {'counts': 1, 'layout_z': 19.559980709635155, 'model_weight': 7.79, 'order_id': 933877, 'pid': 399902, 'print_id': 140265}, {'counts': 1, 'layout_z': 16.488399505615234, 'model_weight': 5.349, 'order_id': 933882, 'pid': 399907, 'print_id': 140271}, {'counts': 1, 'layout_z': 18.02717763893993, 'model_weight': 5.892, 'order_id': 933885, 'pid': 399910, 'print_id': 140277}, {'counts': 1, 'layout_z': 26.876644549545638, 'model_weight': 21.486, 'order_id': 933886, 'pid': 399911, 'print_id': 140278}, {'counts': 1, 'layout_z': 28.074640440717047, 'model_weight': 16.17, 'order_id': 933887, 'pid': 399912, 'print_id': 140280}, {'counts': 1, 'layout_z': 27.306154248118705, 'model_weight': 20.977, 'order_id': 933889, 'pid': 399927, 'print_id': 140281}, {'counts': 1, 'layout_z': 26.094746051465723, 'model_weight': 34.197, 'order_id': 933888, 'pid': 399926, 'print_id': 140282}, {'counts': 1, 'layout_z': 15.87796963527322, 'model_weight': 4.735, 'order_id': 933892, 'pid': 399930, 'print_id': 140287}, {'counts': 1, 'layout_z': 18.191209446277444, 'model_weight': 5.246, 'order_id': 933893, 'pid': 399931, 'print_id': 140288}, {'counts': 1, 'layout_z': 17.777126572389776, 'model_weight': 6.334, 'order_id': 933894, 'pid': 399932, 'print_id': 140289}, {'counts': 1, 'layout_z': 17.58385879418167, 'model_weight': 5.8, 'order_id': 933895, 'pid': 399933, 'print_id': 140290}, {'counts': 1, 'layout_z': 18.593739251800994, 'model_weight': 6.955, 'order_id': 933897, 'pid': 399935, 'print_id': 140293}, {'counts': 1, 'layout_z': 14.231568581173965, 'model_weight': 3.705, 'order_id': 933898, 'pid': 399936, 'print_id': 140294}, {'counts': 1, 'layout_z': 13.998784146949038, 'model_weight': 3.533, 'order_id': 933899, 'pid': 399937, 'print_id': 140295}, {'counts': 1, 'layout_z': 15.9964307861582, 'model_weight': 4.301, 'order_id': 933901, 'pid': 399939, 'print_id': 140297}, {'counts': 1, 'layout_z': 16.18931739014667, 'model_weight': 5.019, 'order_id': 933903, 'pid': 399941, 'print_id': 140299}, {'counts': 1, 'layout_z': 24.79611153168641, 'model_weight': 20.601, 'order_id': 933905, 'pid': 399943, 'print_id': 140301}, {'counts': 1, 'layout_z': 24.306803898330127, 'model_weight': 16.784, 'order_id': 933906, 'pid': 399944, 'print_id': 140302}, {'counts': 1, 'layout_z': 29.3158714015686, 'model_weight': 19.351, 'order_id': 933907, 'pid': 399945, 'print_id': 140303}, {'counts': 1, 'layout_z': 17.005620048049607, 'model_weight': 5.169, 'order_id': 933910, 'pid': 399948, 'print_id': 140305}, {'counts': 1, 'layout_z': 16.464274211211865, 'model_weight': 4.866, 'order_id': 933909, 'pid': 399947, 'print_id': 140306}, {'counts': 1, 'layout_z': 23.198866489386088, 'model_weight': 10.524, 'order_id': 933911, 'pid': 399949, 'print_id': 140307}, {'counts': 1, 'layout_z': 26.516445616407367, 'model_weight': 23.957, 'order_id': 933912, 'pid': 399950, 'print_id': 140308}, {'counts': 1, 'layout_z': 17.937848519147412, 'model_weight': 5.282, 'order_id': 933914, 'pid': 399952, 'print_id': 140310}, {'counts': 1, 'layout_z': 26.754205819816015, 'model_weight': 20.607, 'order_id': 933921, 'pid': 399957, 'print_id': 140315}, {'counts': 1, 'layout_z': 20.002697843362704, 'model_weight': 7.63, 'order_id': 933924, 'pid': 399960, 'print_id': 140318}, {'counts': 1, 'layout_z': 30.231639651233593, 'model_weight': 24.508, 'order_id': 933925, 'pid': 399961, 'print_id': 140319}, {'counts': 1, 'layout_z': 16.061075531610975, 'model_weight': 4.195, 'order_id': 933928, 'pid': 399964, 'print_id': 140320}, {'counts': 1, 'layout_z': 15.115618198253117, 'model_weight': 3.217, 'order_id': 933929, 'pid': 399965, 'print_id': 140323}, {'counts': 1, 'layout_z': 20.147708222788964, 'model_weight': 7.246, 'order_id': 933960, 'pid': 400001, 'print_id': 140325}, {'counts': 1, 'layout_z': 16.839157818561507, 'model_weight': 5.147, 'order_id': 933962, 'pid': 400003, 'print_id': 140327}, {'counts': 1, 'layout_z': 18.260445870716055, 'model_weight': 5.598, 'order_id': 933963, 'pid': 400004, 'print_id': 140328}, {'counts': 1, 'layout_z': 15.999999046325684, 'model_weight': 4.16, 'order_id': 933964, 'pid': 400005, 'print_id': 140329}, {'counts': 1, 'layout_z': 23.418245000534494, 'model_weight': 15.579, 'order_id': 933967, 'pid': 400008, 'print_id': 140333}, {'counts': 1, 'layout_z': 28.939651438044436, 'model_weight': 31.598, 'order_id': 933970, 'pid': 400024, 'print_id': 140335}, {'counts': 1, 'layout_z': 14.9528131844746, 'model_weight': 3.438, 'order_id': 933972, 'pid': 400026, 'print_id': 140337}, {'counts': 1, 'layout_z': 14.919241260134326, 'model_weight': 4.573, 'order_id': 933974, 'pid': 400028, 'print_id': 140340}, {'counts': 1, 'layout_z': 17.26018167267985, 'model_weight': 5.882, 'order_id': 933975, 'pid': 400029, 'print_id': 140342}, {'counts': 1, 'layout_z': 28.157231966147624, 'model_weight': 25.408, 'order_id': 933976, 'pid': 400030, 'print_id': 140343}, {'counts': 1, 'layout_z': 28.3214832027494, 'model_weight': 21.904, 'order_id': 933977, 'pid': 400031, 'print_id': 140344}, {'counts': 1, 'layout_z': 23.17201737455146, 'model_weight': 14.336, 'order_id': 933979, 'pid': 400033, 'print_id': 140346}, {'counts': 1, 'layout_z': 4.562267065048218, 'model_weight': 12.343, 'order_id': 933577, 'pid': 399494, 'print_id': 140676}, {'counts': 1, 'layout_z': 27.36789647731373, 'model_weight': 28.917, 'order_id': 932799, 'pid': 397657, 'print_id': 141912}, {'counts': 1, 'layout_z': 6.184627175331121, 'model_weight': 23.683, 'order_id': 932029, 'pid': 397140, 'print_id': 141954}, {'counts': 1, 'layout_z': 28.632703110041838, 'model_weight': 29.224, 'order_id': 933097, 'pid': 398980, 'print_id': 142034}, {'counts': 1, 'layout_z': 29.13069982014371, 'model_weight': 38.882, 'order_id': 926254, 'pid': 389047, 'print_id': 142052}, {'counts': 1, 'layout_z': 26.624711034938723, 'model_weight': 20.721, 'order_id': 933136, 'pid': 398998, 'print_id': 142056}, {'counts': 1, 'layout_z': 23.73959009314062, 'model_weight': 30.124, 'order_id': 928988, 'pid': 393851, 'print_id': 142057}, {'counts': 1, 'layout_z': 29.556987644497696, 'model_weight': 23.687, 'order_id': 933093, 'pid': 398975, 'print_id': 142059}]}
 
 test_print_max = 0
 
diff --git a/download_print.py b/download_print.py
index 7812383..023fd26 100644
--- a/download_print.py
+++ b/download_print.py
@@ -1,455 +1,31 @@
-import yaml
 import oss2
 import os
 from tqdm import tqdm
-# from utils.log_utils import log_execution
 import os
 from pathlib import Path
 
-import numpy as np
-import collections
 import os
 import argparse
 
+from dataclasses import dataclass
+
 from config import oss_config
 from config import print_data_dir
 from config import url_get_oss_suffix_by_orderId
+from config import url_get_info_by_print_batch_id
 
 from general import is_use_debug_oss
 from general import transform_save_bpy
+from general import read_models_from_json
+from general import is_small_machine
 
 from compute_print_net import get_oss_client
 
-class DataTransfer:
-    '''
-    数据传输类
-    '''
-    def __init__(self, local_path: str, oss_path: str, oss_client: oss2.Bucket):
-        '''
-        local_path: 本地输出路径
-        oss_path: oss路径
-        oss_client: oss客户端
-        '''
-        self.local_path = local_path
-        self.oss_path = oss_path.lstrip('/')
-        self.oss_client = oss_client
-        # self.description = description
-
-    # @log_execution(self.description)
-    def download_data(self):
-        """
-        从 OSS 下载数据到本地，保持原有目录结构
-        """
-        
-        # 列出所有对象
-        objects = []
-        prefix = self.oss_path.lstrip('/')  # 移除开头的 '/' 以匹配 OSS 格式
-        
-        for obj in oss2.ObjectIterator(self.oss_client, prefix=prefix):
-            if obj.key != prefix:  # 跳过目录本身
-                objects.append(obj.key)
-        
-        # 下载所有文件，添加进度条
-        for obj_key in tqdm(objects, desc="下载进度"):
-            if obj_key.endswith('/'):
-                continue
-
-            if "printId" in obj_key:
-                continue
-
-            # 计算相对路径
-            rel_path = obj_key[len(prefix):].lstrip('/')
-            # 构建本地完整路径
-            local_path = os.path.join(self.local_path, rel_path)
-
-            # 创建必要的目录
-            os.makedirs(os.path.dirname(local_path), exist_ok=True)
-            
-            # 下载文件
-            self.oss_client.get_object_to_file(obj_key, local_path)
-            
-            print("download_data local_path=" + local_path)
-
-    order_id: str
-    pid: str
-    model_height: str
-
-    def download_data_rename_json(self, json_model_info):
-        """
-        从 OSS 下载数据到本地，保持原有目录结构
-        """
-        
-        # 列出所有对象
-        objects = []
-        prefix = self.oss_path.lstrip('/')  # 移除开头的 '/' 以匹配 OSS 格式
-        
-        for obj in oss2.ObjectIterator(self.oss_client, prefix=prefix):
-            if obj.key != prefix:  # 跳过目录本身
-                objects.append(obj.key)
-        
-        # 下载所有文件，添加进度条
-        for obj_key in tqdm(objects, desc="下载进度"):
-            if obj_key.endswith('/'):
-                continue
-
-            if "printId" in obj_key:
-                continue
-
-            # 计算相对路径
-            rel_path = obj_key[len(prefix):].lstrip('/')
-
-            file_dir, file_name = os.path.split(rel_path)
-            file_base, file_ext = os.path.splitext(file_name)
-
-            # 根据文件后缀名进行重命名
-            if file_ext.lower() in ['.mtl', '.jpg', '.jpeg', '.png']:
-                # 对于.mtl和图片文件，在原名前加order_id
-                new_file_name = f"{json_model_info.order_id}_{file_name}"
-                # new_file_name = file_name
-            elif file_ext.lower() == '.obj':
-                # 对于.obj文件，完全重命名
-                new_file_name = f"{json_model_info.obj_name}"
-            else:
-                # 其他文件类型保持原名
-                new_file_name = file_name
-            print("new_file_name=", new_file_name)
-
-            # 构建新的相对路径
-            if file_dir:  # 如果有子目录
-                new_rel_path = os.path.join(file_dir, new_file_name)
-            else:
-                new_rel_path = new_file_name
-
-            # 构建本地完整路径
-            local_path = os.path.join(self.local_path, new_rel_path)
-            
-            # 创建必要的目录
-            os.makedirs(os.path.dirname(local_path), exist_ok=True)
-            
-            # 下载文件
-            self.oss_client.get_object_to_file(obj_key, local_path)
-
-            if file_ext == '.obj':  # 10MB以上
-                try:
-                    # 使用临时文件避免内存问题 [8](@ref)
-                    temp_path = local_path + '.tmp'
-                    with open(local_path, 'r', encoding='utf-8') as f_in, \
-                        open(temp_path, 'w', encoding='utf-8') as f_out:
-                        
-                        mtllib_modified = False
-                        for line in f_in:
-                            if not mtllib_modified and line.strip().startswith('mtllib '):
-                                parts = line.split(' ', 1)
-                                if len(parts) > 1:
-                                    old_mtl_name = parts[1].strip()
-                                    new_mtl_name = f"{json_model_info.order_id}_{old_mtl_name}"
-                                    f_out.write(f"mtllib {new_mtl_name}\n")
-                                    mtllib_modified = True
-                                    continue
-                            f_out.write(line)
-                    
-                    os.replace(temp_path, local_path)  # 原子性替换
-                    
-                except IOError as e:
-                    print(f"处理大文件 {local_path} 时出错: {e}")
-                    if os.path.exists(temp_path):
-                        os.remove(temp_path)
-            
-            # 优化后的.obj文件处理逻辑
-            if file_ext == '.mtl':
-                try:
-                    # 使用更高效的文件读取方式 [6,8](@ref)
-                    with open(local_path, 'r', encoding='utf-8') as f:
-                        content = f.read()
-                    
-                    # 使用字符串方法直接查找和替换，避免不必要的循环 [9](@ref)
-                    lines = content.split('\n')
-                    mtllib_modified = False
-                    
-                    for i, line in enumerate(lines):
-                        stripped_line = line.strip()
-                        if not mtllib_modified and stripped_line.startswith('map_Kd '):
-                            # 更高效的分割方式 [9](@ref)
-                            parts = line.split(' ', 1)
-                            if len(parts) > 1:
-                                old_name = parts[1].strip()
-                                new_name = f"{json_model_info.order_id}_{old_name}"
-                                lines[i] = f"map_Kd {new_name}"
-                                mtllib_modified = True
-                                print(f"已更新材质库引用: {old_name} -> {new_name}")
-                                break  # 找到第一个后立即退出
-                    
-                    # 批量写入，减少I/O操作 [6](@ref)
-                    with open(local_path, 'w', encoding='utf-8') as f:
-                        f.write('\n'.join(lines))
-                        
-                except IOError as e:
-                    print(f"处理文件 {local_path} 时出错: {e}")
-                except UnicodeDecodeError as e:
-                    print(f"文件编码错误 {local_path}: {e}")
-
-            print(f"下载文件: {obj_key} -> {local_path}")
-
-    def download_data_rename_batch(self, batch_model_info):
-        """
-        从 OSS 下载数据到本地，保持原有目录结构
-        """
-        
-        # 列出所有对象
-        objects = []
-        prefix = self.oss_path.lstrip('/')  # 移除开头的 '/' 以匹配 OSS 格式
-
-        prefix_exists = False
-        
-        for obj in oss2.ObjectIterator(self.oss_client, prefix=prefix):
-            prefix_exists = True
-            if obj.key != prefix:  # 跳过目录本身
-                objects.append(obj.key)
-                print(f"obj.key={obj.key}")
-        
-        if not prefix_exists:
-            print(f"前缀 '{prefix}' 下没有找到任何文件或目录。")
-            return False
-        else:
-            print(f"前缀 '{prefix}' 存在，共找到 {len(objects)} 个对象。")
-
-        # 下载所有文件，添加进度条
-        for obj_key in tqdm(objects, desc="下载进度"):
-            if obj_key.endswith('/'):
-                print("下载 endswith('/'")
-                continue
-
-            if "printId" in obj_key:
-                print(f"下载 in obj_key")
-                continue
-
-            # 计算相对路径
-            rel_path = obj_key[len(prefix):].lstrip('/')
-
-            file_dir, file_name = os.path.split(rel_path)
-            file_base, file_ext = os.path.splitext(file_name)
-
-            # 根据文件后缀名进行重命名
-            if file_ext.lower() in ['.mtl', '.jpg', '.jpeg', '.png']:
-                # 对于.mtl和图片文件，在原名前加order_id
-                new_file_name = f"{batch_model_info.order_id}_{file_name}"
-                # new_file_name = file_name
-            elif file_ext.lower() == '.obj':
-                # 对于.obj文件，完全重命名
-                new_file_name = f"{batch_model_info.order_id}_{batch_model_info.pid}_P{batch_model_info.print_order_id}_{batch_model_info.model_size}{file_ext}"
-            else:
-                # 其他文件类型保持原名
-                new_file_name = file_name
-
-            # 构建新的相对路径
-            if file_dir:  # 如果有子目录
-                new_rel_path = os.path.join(file_dir, new_file_name)
-            else:
-                new_rel_path = new_file_name
-
-            # 构建本地完整路径
-            local_path = os.path.join(self.local_path, new_rel_path)
-            
-            # 创建必要的目录
-            os.makedirs(os.path.dirname(local_path), exist_ok=True)
-            
-            # 下载文件
-            self.oss_client.get_object_to_file(obj_key, local_path)
-
-            if file_ext == '.obj':  # 10MB以上
-                try:
-                    # 使用临时文件避免内存问题 [8](@ref)
-                    temp_path = local_path + '.tmp'
-                    with open(local_path, 'r', encoding='utf-8') as f_in, \
-                        open(temp_path, 'w', encoding='utf-8') as f_out:
-                        
-                        mtllib_modified = False
-                        for line in f_in:
-                            if not mtllib_modified and line.strip().startswith('mtllib '):
-                                parts = line.split(' ', 1)
-                                if len(parts) > 1:
-                                    old_mtl_name = parts[1].strip()
-                                    new_mtl_name = f"{batch_model_info.order_id}_{old_mtl_name}"
-                                    f_out.write(f"mtllib {new_mtl_name}\n")
-                                    mtllib_modified = True
-                                    print("len(parts) > 1")
-                                    continue
-                            f_out.write(line)
-                    
-                    os.replace(temp_path, local_path)  # 原子性替换
-                    
-                except IOError as e:
-                    print(f"处理大文件 {local_path} 时出错: {e}")
-                    if os.path.exists(temp_path):
-                        os.remove(temp_path)
-            
-            # 优化后的.obj文件处理逻辑
-            if file_ext == '.mtl':
-                try:
-                    # 使用更高效的文件读取方式 [6,8](@ref)
-                    with open(local_path, 'r', encoding='utf-8') as f:
-                        content = f.read()
-                    
-                    # 使用字符串方法直接查找和替换，避免不必要的循环 [9](@ref)
-                    lines = content.split('\n')
-                    mtllib_modified = False
-                    
-                    for i, line in enumerate(lines):
-                        stripped_line = line.strip()
-                        if not mtllib_modified and stripped_line.startswith('map_Kd '):
-                            # 更高效的分割方式 [9](@ref)
-                            parts = line.split(' ', 1)
-                            if len(parts) > 1:
-                                old_name = parts[1].strip()
-                                new_name = f"{batch_model_info.order_id}_{old_name}"
-                                lines[i] = f"map_Kd {new_name}"
-                                mtllib_modified = True
-                                print(f"已更新材质库引用: {old_name} -> {new_name}")
-                                break  # 找到第一个后立即退出
-                    
-                    # 批量写入，减少I/O操作 [6](@ref)
-                    with open(local_path, 'w', encoding='utf-8') as f:
-                        f.write('\n'.join(lines))
-                        
-                except IOError as e:
-                    print(f"处理文件 {local_path} 时出错: {e}")
-                except UnicodeDecodeError as e:
-                    print(f"文件编码错误 {local_path}: {e}")
-
-            print(f"下载文件: {obj_key} -> {local_path}")
-        
-        return True
-
-    def upload_data(self):
-        '''
-        上传数据到OSS
-        '''
-        # 检测本地路径是否存在
-        if not os.path.exists(self.local_path):
-            raise FileNotFoundError(f"本地路径不存在: {self.local_path}")
-
-        # 判断本地路径是文件还是目录
-        if os.path.isfile(self.local_path):
-            local_suffix = Path(self.local_path).suffix
-            oss_suffix = Path(self.oss_path).suffix
-
-            if oss_suffix and oss_suffix != local_suffix:
-                # 后缀名不一致，上传到指定文件夹下的同名文件
-                oss_dir = os.path.dirname(self.oss_path)
-                oss_target_path = os.path.join(oss_dir, os.path.basename(self.local_path))
-            else:
-                # 后缀名一致，上传到指定OSS路径
-                oss_target_path = self.oss_path
-
-            # 上传文件
-            self.oss_client.put_object_from_file(oss_target_path, self.local_path)
-
-            print(f"文件已上传到: {oss_target_path}")
-
-        elif os.path.isdir(self.local_path):
-            oss_suffix = Path(self.oss_path).suffix
-            if oss_suffix:
-                raise ValueError("不能将目录上传到具有后缀名的OSS路径。")
-
-            # 遍历本地目录并上传
-            for root, dirs, files in os.walk(self.local_path):
-                for file in files:
-                    local_file_path = os.path.join(root, file)
-                    relative_path = os.path.relpath(local_file_path, self.local_path)
-                    oss_file_path = os.path.join(self.oss_path, relative_path).replace("\\", "/")
-                    
-                    # 创建必要的目录
-                    oss_dir = os.path.dirname(oss_file_path)
-                    
-                    # 上传文件
-                    self.oss_client.put_object_from_file(oss_file_path, local_file_path)
-                    print(f"文件已上传到: {oss_file_path}")
-        else:
-            raise ValueError(f"无效的本地路径类型: {self.local_path}")
+from download_print_out import DataTransfer
+from download_print_out import download_data_by_json
 
 import requests
-import json
 import shutil
-    
-from dataclasses import dataclass
-@dataclass
-class JSONModelInfo:
-    obj_name: str
-    order_id: str
-    pid: str
-    model_height: str
-
-def read_pids_from_json(pid_file):
-    """从文件读取所有PID"""
-    # with open(pid_file, 'r') as f:
-    #     # 过滤掉空行并去除每行首尾的空白字符
-    #     return [line.strip() for line in f if line.strip()]
-
-    json_path = pid_file
-
-    """
-    加载JSON文件，读取所有模型信息，应用变换后返回模型列表
-    """
-    # 检查JSON文件是否存在
-    if not os.path.exists(json_path):
-        print(f"错误: JSON文件不存在 - {json_path}")
-        return []
-    
-    # 读取JSON文件
-    try:
-        with open(json_path, 'r') as f:
-            data = json.load(f)
-    except Exception as e:
-        print(f"读取JSON文件失败: {e}")
-        return []
-    
-    list_model_info = []
-    # 处理每个模型
-    for model in data.get('models', []):
-        obj_name = model.get('file_name', '')
-
-        parts = obj_name.split('_')
-
-        order_id = parts[0]
-        pid = parts[1]
-        model_height = parts[3]
-
-        model_info = JSONModelInfo(
-            obj_name=obj_name,
-            order_id=order_id,
-            pid=pid,
-            model_height=model_height
-        )
-        list_model_info.append(model_info)
-    
-    return list_model_info, data
-
-def download_data_by_json(model_info, workdir, oss_client ):
-    try:
-        pid = model_info.pid
-        model_height = model_info.model_height
-        target_dir = f"{workdir}"
-
-        url = f"{url_get_oss_suffix_by_orderId}{model_info.order_id}"
-        res = requests.get(url)
-
-        data = res.json()["data"]
-        # print("datas=",data)
-        data = data.replace("/init_obj", "")
-
-        print("target_dir=", target_dir)
-        # download_textures = DataTransfer(target_dir, f"objs/download/print/{pid}/base/model/{model_height}/", oss_client)
-        # download_textures = DataTransfer(target_dir, f"objs/download/print/{pid}/base_cartoon/badge/101/3/{model_height}/", oss_client)
-        download_textures = DataTransfer(target_dir, f"objs/download/print/{pid}/{data}/{model_height}/", oss_client)
-
-        download_textures.download_data_rename_json(model_info)
-        # 下载后检查目标文件夹是否为空
-        if os.path.exists(target_dir) and not os.listdir(target_dir):
-            shutil.rmtree(target_dir)
-            print(f"下载后检查发现目标文件夹为空，已删除: {target_dir}")
-    except Exception as e:
-        print(f"卡通图片下载失败: {pid}, 错误: {str(e)}")
-        pass
 
 @dataclass
 class BatchModelInfo:
@@ -461,8 +37,8 @@ class BatchModelInfo:
     count: str
 
 def read_paths_from_batch(batch_id):
-    url = f"https://mp.api.suwa3d.com/api/printOrder/getInfoByPrintBatchId?batch_id={batch_id}"
-    res = requests.get(url)
+    
+    res = requests.get(f"{url_get_info_by_print_batch_id}{batch_id}")
 
     datas = res.json()["data"]
     print("datas=",datas)
@@ -528,35 +104,19 @@ def download_datas_by_pre_layout(list_print_model_info, workdir, oss_config):
             return False
     return True
 
-def download_transform_save_by_batch(batch_id, workdir, oss_config):
-    datas, succ = download_datas_by_batch(batch_id, workdir, oss_config)
-    print("datas=", datas)
-    layout_data = datas["layout_data"]
-
-    original_obj_pid_dir = workdir
-
-    transform_save_o3d(layout_data, original_obj_pid_dir)
-
 def download_datas_by_json(json_name, workdir, oss_config):
     oss_client = get_oss_client(oss_config)
 
-    #json_path = os.path.join(workdir, "3DPrintLayout.json")
     json_path = os.path.join(workdir, f"{json_name}.json")
     
-    # 读取所有PID
-    list_model_info, data = read_pids_from_json(json_path)
-    print(f"从文件读取了 {len(list_model_info)} 个PID")
+    list_model_info, json_data = read_models_from_json(json_path)
+    print(f"从文件读取了 {len(list_model_info)} 个model")
     # 批量下载
     for model_info in list_model_info:
         print(f"开始下载PID: {model_info}")
         download_data_by_json(model_info, workdir, oss_client)
 
-    return data
-
-def download_transform_save_by_json(json_name, workdir, oss_config):
-    layout_data = download_datas_by_json(json_name, workdir, oss_config)
-    original_obj_pid_dir = workdir
-    transform_save_bpy(layout_data, original_obj_pid_dir)
+    return json_data
 
 def upload_result(base_original_obj_dir, oss_config, batch_id):
 
@@ -580,13 +140,10 @@ def upload_result(base_original_obj_dir, oss_config, batch_id):
         print(f"失败: {batch_id}, 错误: {str(e)}")
         pass
         
-import open3d as o3d
-
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
 
-    is_by_batch = True
-    is_transform_save = False
+    is_by_batch = False
     batch_id = 10118 
     if is_by_batch:
         # 通过batch_id下载
@@ -599,11 +156,11 @@ if __name__ == "__main__":
 
         workdir = f"{print_data_dir}{batch_id}"
 
+        is_transform_save = False
+        datas, succ = download_datas_by_batch(batch_id, workdir, oss_config)
         if is_transform_save:
-            download_transform_save_by_batch(batch_id, workdir, oss_config)
-        else:
-            download_datas_by_batch(batch_id, workdir, oss_config)
-            
+            layout_data = datas["layout_data"]
+            transform_save_bpy(layout_data, workdir)
     else:
         # 通过Json下载
 
@@ -617,7 +174,6 @@ if __name__ == "__main__":
 
         json_name = batch_id
 
-        if is_transform_save:
-            download_transform_save_by_json(json_name, workdir, oss_config)
-        else:
-            download_datas_by_json(json_name, workdir, oss_config)
\ No newline at end of file
+        json_data = download_datas_by_json(json_name, workdir, oss_config)
+        if is_small_machine(json_data):
+            transform_save_bpy(json_data, workdir)
diff --git a/download_print_out.py b/download_print_out.py
index 83f4c28..530fede 100644
--- a/download_print_out.py
+++ b/download_print_out.py
@@ -5,10 +5,12 @@ import os
 import numpy as np
 import os
 import argparse
-import bpy
+# import bpy
 import sys
 import open3d as o3d
 
+from pathlib import Path
+
 import requests
 import json
 import shutil
@@ -16,6 +18,7 @@ import shutil
 from config import url_get_oss_suffix_by_orderId
 
 from general import transform_save_bpy
+from general import read_models_from_json
 
 from compute_print_net import get_oss_client
 
@@ -37,6 +40,46 @@ class DataTransfer:
         self.local_path = local_path
         self.oss_path = oss_path.lstrip('/')
         self.oss_client = oss_client
+        # self.description = description
+
+    # @log_execution(self.description)
+    def download_data(self):
+        """
+        从 OSS 下载数据到本地，保持原有目录结构
+        """
+        
+        # 列出所有对象
+        objects = []
+        prefix = self.oss_path.lstrip('/')  # 移除开头的 '/' 以匹配 OSS 格式
+        
+        for obj in oss2.ObjectIterator(self.oss_client, prefix=prefix):
+            if obj.key != prefix:  # 跳过目录本身
+                objects.append(obj.key)
+        
+        # 下载所有文件，添加进度条
+        for obj_key in tqdm(objects, desc="下载进度"):
+            if obj_key.endswith('/'):
+                continue
+
+            if "printId" in obj_key:
+                continue
+
+            # 计算相对路径
+            rel_path = obj_key[len(prefix):].lstrip('/')
+            # 构建本地完整路径
+            local_path = os.path.join(self.local_path, rel_path)
+
+            # 创建必要的目录
+            os.makedirs(os.path.dirname(local_path), exist_ok=True)
+            
+            # 下载文件
+            self.oss_client.get_object_to_file(obj_key, local_path)
+            
+            print("download_data local_path=" + local_path)
+
+    order_id: str
+    pid: str
+    model_height: str
 
     def download_data_rename_json(self, json_model_info):
         """
@@ -154,6 +197,197 @@ class DataTransfer:
 
             print(f"下载文件: {obj_key} -> {local_path}")
 
+    def download_data_rename_batch(self, batch_model_info):
+        """
+        从 OSS 下载数据到本地，保持原有目录结构
+        """
+        
+        # 列出所有对象
+        objects = []
+        prefix = self.oss_path.lstrip('/')  # 移除开头的 '/' 以匹配 OSS 格式
+
+        prefix_exists = False
+        
+        for obj in oss2.ObjectIterator(self.oss_client, prefix=prefix):
+            prefix_exists = True
+            if obj.key != prefix:  # 跳过目录本身
+                objects.append(obj.key)
+                print(f"obj.key={obj.key}")
+        
+        if not prefix_exists:
+            print(f"前缀 '{prefix}' 下没有找到任何文件或目录。")
+            return False
+        else:
+            print(f"前缀 '{prefix}' 存在，共找到 {len(objects)} 个对象。")
+
+        # 下载所有文件，添加进度条
+        for obj_key in tqdm(objects, desc="下载进度"):
+            if obj_key.endswith('/'):
+                print("下载 endswith('/'")
+                continue
+
+            if "printId" in obj_key:
+                print(f"下载 in obj_key")
+                continue
+
+            # 计算相对路径
+            rel_path = obj_key[len(prefix):].lstrip('/')
+
+            file_dir, file_name = os.path.split(rel_path)
+            file_base, file_ext = os.path.splitext(file_name)
+
+            # 根据文件后缀名进行重命名
+            if file_ext.lower() in ['.mtl', '.jpg', '.jpeg', '.png']:
+                # 对于.mtl和图片文件，在原名前加order_id
+                new_file_name = f"{batch_model_info.order_id}_{file_name}"
+                # new_file_name = file_name
+            elif file_ext.lower() == '.obj':
+                # 对于.obj文件，完全重命名
+                new_file_name = f"{batch_model_info.order_id}_{batch_model_info.pid}_P{batch_model_info.print_order_id}_{batch_model_info.model_size}{file_ext}"
+            else:
+                # 其他文件类型保持原名
+                new_file_name = file_name
+
+            # 构建新的相对路径
+            if file_dir:  # 如果有子目录
+                new_rel_path = os.path.join(file_dir, new_file_name)
+            else:
+                new_rel_path = new_file_name
+
+            # 构建本地完整路径
+            local_path = os.path.join(self.local_path, new_rel_path)
+            
+            # 创建必要的目录
+            os.makedirs(os.path.dirname(local_path), exist_ok=True)
+            
+            # 下载文件
+            self.oss_client.get_object_to_file(obj_key, local_path)
+
+            if file_ext == '.obj':  # 10MB以上
+                try:
+                    # 使用临时文件避免内存问题 [8](@ref)
+                    temp_path = local_path + '.tmp'
+                    with open(local_path, 'r', encoding='utf-8') as f_in, \
+                        open(temp_path, 'w', encoding='utf-8') as f_out:
+                        
+                        mtllib_modified = False
+                        for line in f_in:
+                            if not mtllib_modified and line.strip().startswith('mtllib '):
+                                parts = line.split(' ', 1)
+                                if len(parts) > 1:
+                                    old_mtl_name = parts[1].strip()
+                                    new_mtl_name = f"{batch_model_info.order_id}_{old_mtl_name}"
+                                    f_out.write(f"mtllib {new_mtl_name}\n")
+                                    mtllib_modified = True
+                                    print("len(parts) > 1")
+                                    continue
+                            f_out.write(line)
+                    
+                    os.replace(temp_path, local_path)  # 原子性替换
+                    
+                except IOError as e:
+                    print(f"处理大文件 {local_path} 时出错: {e}")
+                    if os.path.exists(temp_path):
+                        os.remove(temp_path)
+            
+            # 优化后的.obj文件处理逻辑
+            if file_ext == '.mtl':
+                try:
+                    # 使用更高效的文件读取方式 [6,8](@ref)
+                    with open(local_path, 'r', encoding='utf-8') as f:
+                        content = f.read()
+                    
+                    # 使用字符串方法直接查找和替换，避免不必要的循环 [9](@ref)
+                    lines = content.split('\n')
+                    mtllib_modified = False
+                    
+                    for i, line in enumerate(lines):
+                        stripped_line = line.strip()
+                        if not mtllib_modified and stripped_line.startswith('map_Kd '):
+                            # 更高效的分割方式 [9](@ref)
+                            parts = line.split(' ', 1)
+                            if len(parts) > 1:
+                                old_name = parts[1].strip()
+                                new_name = f"{batch_model_info.order_id}_{old_name}"
+                                lines[i] = f"map_Kd {new_name}"
+                                mtllib_modified = True
+                                print(f"已更新材质库引用: {old_name} -> {new_name}")
+                                break  # 找到第一个后立即退出
+                    
+                    # 批量写入，减少I/O操作 [6](@ref)
+                    with open(local_path, 'w', encoding='utf-8') as f:
+                        f.write('\n'.join(lines))
+                        
+                except IOError as e:
+                    print(f"处理文件 {local_path} 时出错: {e}")
+                except UnicodeDecodeError as e:
+                    print(f"文件编码错误 {local_path}: {e}")
+
+            print(f"下载文件: {obj_key} -> {local_path}")
+        
+        return True
+
+    def download_single_file(self):
+        """
+        下载单个文件从OSS到本地
+        """
+        # 确保本地目录存在
+        os.makedirs(os.path.dirname(self.local_path), exist_ok=True)
+        
+        # 直接下载文件
+        try:
+            self.oss_client.get_object_to_file(self.oss_path, self.local_path)
+            print(f"文件已下载到: {self.local_path}")
+        except oss2.exceptions.NoSuchKey:
+            print(f"OSS文件不存在: {self.oss_path}")
+
+    def upload_data(self):
+        '''
+        上传数据到OSS
+        '''
+        # 检测本地路径是否存在
+        if not os.path.exists(self.local_path):
+            raise FileNotFoundError(f"本地路径不存在: {self.local_path}")
+
+        # 判断本地路径是文件还是目录
+        if os.path.isfile(self.local_path):
+            local_suffix = Path(self.local_path).suffix
+            oss_suffix = Path(self.oss_path).suffix
+
+            if oss_suffix and oss_suffix != local_suffix:
+                # 后缀名不一致，上传到指定文件夹下的同名文件
+                oss_dir = os.path.dirname(self.oss_path)
+                oss_target_path = os.path.join(oss_dir, os.path.basename(self.local_path))
+            else:
+                # 后缀名一致，上传到指定OSS路径
+                oss_target_path = self.oss_path
+
+            # 上传文件
+            self.oss_client.put_object_from_file(oss_target_path, self.local_path)
+
+            print(f"文件已上传到: {oss_target_path}")
+
+        elif os.path.isdir(self.local_path):
+            oss_suffix = Path(self.oss_path).suffix
+            if oss_suffix:
+                raise ValueError("不能将目录上传到具有后缀名的OSS路径。")
+
+            # 遍历本地目录并上传
+            for root, dirs, files in os.walk(self.local_path):
+                for file in files:
+                    local_file_path = os.path.join(root, file)
+                    relative_path = os.path.relpath(local_file_path, self.local_path)
+                    oss_file_path = os.path.join(self.oss_path, relative_path).replace("\\", "/")
+                    
+                    # 创建必要的目录
+                    oss_dir = os.path.dirname(oss_file_path)
+                    
+                    # 上传文件
+                    self.oss_client.put_object_from_file(oss_file_path, local_file_path)
+                    print(f"文件已上传到: {oss_file_path}")
+        else:
+            raise ValueError(f"无效的本地路径类型: {self.local_path}")
+
 def get_api(url):
     try:
         response = requests.get(url)
@@ -166,61 +400,6 @@ def get_api(url):
     except requests.exceptions.RequestException as e:
         raise Exception(f"Error fetching URL {url}: {e}")
     
-from dataclasses import dataclass
-@dataclass
-class JSONModelInfo:
-    obj_name: str
-    order_id: str
-    pid: str
-    print_order_id: str
-    model_height: str
-
-def read_pids_from_json(pid_file):
-    """从文件读取所有PID"""
-
-    json_path = pid_file
-
-    """
-    加载JSON文件，读取所有模型信息，应用变换后返回模型列表
-    """
-    # 检查JSON文件是否存在
-    if not os.path.exists(json_path):
-        print(f"错误: JSON文件不存在 - {json_path}")
-        return []
-    
-    # 读取JSON文件
-    try:
-        with open(json_path, 'r') as f:
-            data = json.load(f)
-    except Exception as e:
-        print(f"读取JSON文件失败: {e}")
-        return []
-    
-    list_model_info = []
-    # 处理每个模型
-    for model in data.get('models', []):
-        obj_name = model.get('file_name', '')
-
-        parts = obj_name.split('_')
-
-        order_id = parts[0]
-        pid = parts[1]
-        print_order_id = parts[2]
-        print_order_id = print_order_id.replace("P", "")
-        model_height = parts[3]
-
-        model_info = JSONModelInfo(
-            obj_name=obj_name,
-            order_id=order_id,
-            pid=pid,
-            print_order_id=print_order_id,
-            model_height=model_height
-        )
-        list_model_info.append(model_info)
-        print(f"model_info={model_info}")
-    
-    return list_model_info, data
-
 def download_data_by_json(model_info, workdir, oss_client ):
     try:
         pid = model_info.pid
@@ -249,18 +428,17 @@ def download_data_by_json(model_info, workdir, oss_client ):
 def download_datas_by_json(pid_file, workdir, oss_config):
     oss_client = get_oss_client(oss_config)
 
-    # json_path = os.path.join(workdir, "3DPrintLayout.json")
     json_path = os.path.join(workdir, f"{pid_file}.json")
     
     # 读取所有PID
-    list_model_info, data = read_pids_from_json(json_path)
+    list_model_info, json_data = read_models_from_json(json_path)
     print(f"从文件读取了 {len(list_model_info)} 个PID")
     # 批量下载
     for model_info in list_model_info:
         print(f"开始下载PID: {model_info}")
         download_data_by_json(model_info, args.workdir, oss_client)
 
-    return data
+    return json_data
 
 if __name__ == "__main__":
 
diff --git a/general.py b/general.py
index f10b21a..03fb858 100644
--- a/general.py
+++ b/general.py
@@ -218,3 +218,69 @@ def is_cross_border_c(x, y, z, mx, my, mz, max_x, max_y, max_z):
         return False
 
 # -------------------------- 结束：碰撞检测和越界 --------------------------
+
+# -------------------------- 开始：JSON --------------------------
+
+import json
+from dataclasses import dataclass
+
+@dataclass
+class JSONModelInfo:
+    obj_name: str
+    order_id: str
+    pid: str
+    print_order_id: str
+    model_height: str
+
+def read_from_json(json_path):
+
+    if not os.path.exists(json_path):
+        print(f"错误: JSON文件不存在 - {json_path}")
+        return []
+    
+    try:
+        with open(json_path, 'r') as f:
+            json_data = json.load(f)
+    except Exception as e:
+        print(f"读取JSON文件失败: {e}")
+        return []
+    
+    return json_data
+
+def read_models_from_json(json_path):
+    
+    json_data = read_from_json(json_path)
+    
+    list_model_info = []
+    # 处理每个模型
+    for model in json_data.get('models', []):
+        obj_name = model.get('file_name', '')
+
+        parts = obj_name.split('_')
+
+        order_id = parts[0]
+        pid = parts[1]
+        model_height = parts[3]
+
+        model_info = JSONModelInfo(
+            obj_name=obj_name,
+            order_id=order_id,
+            pid=pid,
+            model_height=model_height
+        )
+        list_model_info.append(model_info)
+    
+    return list_model_info, json_data
+
+def get_summary(json_data):
+    return json_data.get('summary')
+
+def get_selected_machine(json_data):
+    return get_summary(json_data)['selected_machine']
+
+def is_small_machine(json_data):
+    selected_machine = get_selected_machine(json_data)
+    is_small_machine = True if selected_machine=="小机型" else False
+    return is_small_machine
+
+# -------------------------- 结束：JSON --------------------------
diff --git a/test_load_json.py b/test_load_json.py
index 0539e5e..0320742 100644
--- a/test_load_json.py
+++ b/test_load_json.py
@@ -8,6 +8,7 @@ import gc
 
 from config import print_data_dir
 from config import test_print_max
+from config import version
 
 from general import mesh_transform_by_matrix
 from general import get_blank_path
@@ -425,6 +426,8 @@ def set_orthographic(meshes, width=1920, height=1080,
 
     return vis
 
+from PIL import Image, ImageDraw, ImageFont
+
 def render_to_texture(meshes, output_image_path):
 
     vis = set_orthographic(meshes)
@@ -432,6 +435,49 @@ def render_to_texture(meshes, output_image_path):
     # 渲染并保存
     vis.capture_screen_image(output_image_path, do_render=True)
     
+    text = f"v {version}"    # 使用PIL添加文字
+    try:
+        image = Image.open(output_image_path)
+        draw = ImageDraw.Draw(image)
+        
+        font =  ImageFont.load_default()
+
+        font_families = [
+            'DejaVu Sans',    # 许多 Linux 发行版的标准配置[2,5](@ref)
+            'Liberation Sans', # 作为 Arial 等字体的开源替代，预装可能性高[1](@ref)
+            'Ubuntu',          # Ubuntu 系统默认字体之一[3,5](@ref)
+            'FreeSans',        # 另一个开源无衬线字体
+            'Source Sans Pro'  # 一款清晰易读的开源字体
+        ]
+
+        for font_family in font_families:
+            try:
+                font = ImageFont.truetype(font_family, 30)
+                break
+            except IOError:
+                continue
+        
+        bbox = draw.textbbox((0, 0), text, font=font)
+        text_width = bbox[2] - bbox[0]
+        text_height = bbox[3] - bbox[1]
+        
+        # 设置位置：左下角，左边距50像素，下边距10像素[1,3](@ref)
+        width, height = image.size
+        x = 50  # 左边距
+        y = height - text_height - 50  # 图片高度减去文字高度再减去10像素边距
+        
+        fill_color = (255, 0, 0)  
+        
+        # 添加文字
+        draw.text((x, y), text, fill=fill_color, font=font)
+        
+        # 保存带文字的图片
+        image.save(output_image_path)
+        print(f"带文字的渲染图片已保存到: {output_image_path}")
+        
+    except Exception as e:
+        print(f"添加文字时出错: {e}")
+
     print(f"高级渲染图片已保存到: {output_image_path}")
 
     return vis