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4e8ba476f5
| Author | SHA1 | Date | |
|---|---|---|---|
 hesuicong
|
4e8ba476f5 | ||
|
hesuicong
|
4dffb90613 |
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@@ -172,11 +172,9 @@ def get_lowest_position_of_z_ext(mesh_obj):
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vertices = np.asarray(pcd_transformed.vertices)
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z_mean1 = np.mean(vertices[:, 2])
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z_max1 = np.max(vertices[:, 2])
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start_time_v1 = time.time()
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volume_centroid = get_volume_centroid(pcd_transformed)
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z_volume_center1 = volume_centroid[2]
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delta = time.time() - start_time_v1
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# print(f"get_volume_centroid time={delta}")
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angle_rad = np.pi
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#print("旋转前质心:", pcd_transformed.get_center())
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@@ -489,14 +487,14 @@ def arrange_box_correctly(obj_transformed, voxel_size,total_matrix):
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pcd.points = o3d.utility.Vector3dVector(vertices)
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# 降采样与特征计算
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pcd_downsampled = down_sample(pcd, voxel_size)
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# pcd_downsampled = down_sample(pcd, voxel_size)
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# points = np.asarray(pcd_downsampled.points)
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points = np.asarray(pcd.points)
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points = np.asarray(pcd_downsampled.points)
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cov = np.cov(points.T)
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center = obj_transformed.get_center()
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# 特征分解与方向约束（关键修改点）
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eigen_vals, eigen_vecs = np.linalg.eigh(cov)
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max_axis = eigen_vecs[:, np.argmax(eigen_vals)]
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@@ -732,7 +730,7 @@ class Platform:
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else:
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start_y = my + extend_dist_border_y_min
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final_y = self.depth
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print("final_y2", model['name'], start_y, final_y, my, extend_dist_border_y_max, px)
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# print("final_y2", model['name'], start_y, final_y, my, extend_dist_border_y_max, px)
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for y in range(start_y, final_y, +1):
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if self.can_place(px, y, z, model)==False:
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y -= 1
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@@ -24,6 +24,7 @@ redis_config = {
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url_send_layout = 'https://mp.api.suwa3d.com/api/printTypeSettingOrder/printTypeSettingOrderSuccess'
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url_get_info_by_printIds = "https://mp.api.suwa3d.com/api/printOrder/getInfoByPrintIds?print_ids="
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url_get_oss_suffix_by_orderId = f"https://mp.api.suwa3d.com/api/order/getOssSuffixByOrderId?order_id="
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# -------------------------- 结束：网络配置 -------------------------------
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@@ -47,6 +48,8 @@ small_machine_size = [380, 345, 250]
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# 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': 37Line truncated
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# 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}]}
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local_data= {'machine_print_counts': 130, 'machine_type': 'big_machine', 'pre_batch_id': 10188, '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, 'print_id': 134185}, {'counts': 1, 'layout_z': 46.23669371110479, 'model_weight': 56.196, 'order_id': 926778, 'pid': 389918, 'print_id': 134186}, {'counts': 1, 'layout_z': 24.822566986083984, 'model_weight': 31.522, 'order_id': 926268, 'pid': 389067, 'print_id': 134211}, {'counts': 1, 'layout_z': 25.085425667575343, 'model_weight': 31.077, 'order_id': 926267, 'pid': 389066, 'print_id': 134212}, {'counts': 1, 'layout_z': 18.154759649173364, 'model_weight': 6.256, 'order_id': 927059, 'pid': 390269, 'print_id': 134216}, {'counts': 1, 'layout_z': 24.2420189021486, 'model_weight': 14.472, 'order_id': 927065, 'pid': 390275, 'print_id': 134220}, {'counts': 1, 'layout_z': 16.757099114319693, 'model_weight': 5.335, 'order_id': 927078, 'pid': 390299, 'print_id': 134226}, {'counts': 1, 'layout_z': 18.796780948141503, 'model_weight': 7.295, 'order_id': 927079, 'pid': 390300, 'print_id': 134228}, {'counts': 1, 'layout_z': 17.920740666248633, 'model_weight': 7.869, 'order_id': 927082, 'pid': 390303, 'print_id': 134229}, {'counts': 1, 'layout_z': 16.320665859825066, 'model_weight': 4.73, 'order_id': 927081, 'pid': 390302, 'print_id': 134230}, {'counts': 1, 'layout_z': 23.250497020255544, 'model_weight': 15.567, 'order_id': 927100, 'pid': 390331, 'print_id': 134242}, {'counts': 1, 'layout_z': 26.276874511435977, 'model_weight': 19.813, 'order_id': 927103, 'pid': 390334, 'print_id': 134246}, {'counts': 1, 'layout_z': 17.08049576865031, 'model_weight': 5.858, 'order_id': 927111, 'pid': 390342, 'print_id': 134254}, {'counts': 1, 'layout_z': 19.196685578562278, 'model_weight': 6.465, 'order_id': 927117, 'pid': 390347, 'print_id': 134261}, {'counts': 1, 'layout_z': 26.507062216602122, 'model_weight': 14.287, 'order_id': 927116, 'pid': 390346, 'print_id': 134262}, {'counts': 1, 'layout_z': 16.440782827635232, 'model_weight': 5.493, 'order_id': 927118, 'pid': 390348, 'print_id': 134263}, {'counts': 1, 'layout_z': 41.42868301509347, 'model_weight': 68.274, 'order_id': 927122, 'pid': 390354, 'print_id': 134264}, {'counts': 1, 'layout_z': 15.705368176518945, 'model_weight': 4.423, 'order_id': 927119, 'pid': 390349, 'print_id': 134265}, {'counts': 1, 'layout_z': 16.363223697461702, 'model_weight': 5.634, 'order_id': 927120, 'pid': 390351, 'print_id': 134266}, {'counts': 1, 'layout_z': 24.653417686230497, 'model_weight': 17.851, 'order_id': 927121, 'pid': 390353, 'print_id': 134267}, {'counts': 1, 'layout_z': 24.327745611835496, 'model_weight': 28.23, 'order_id': 926040, 'pid': 388832, 'print_id': 134268}, {'counts': 1, 'layout_z': 27.301779030909188, 'model_weight': 23.926, 'order_id': 923281, 'pid': 385001, 'print_id': 134269}, {'counts': 1, 'layout_z': 25.869120288866796, 'model_weight': 32.329, 'order_id': 926077, 'pid': 388864, 'print_id': 134270}, {'counts': 1, 'layout_z': 36.37214874852985, 'model_weight': 65.744, 'order_id': 926086, 'pid': 388873, 'print_id': 134271}, {'counts': 1, 'layout_z': 37.44403689090713, 'model_weight': 80.67, 'order_id': 926097, 'pid': 388884, 'print_id': 134273}, {'counts': 1, 'layout_z': 27.890566642299536, 'model_weight': 22.715, 'order_id': 927127, 'pid': 390372, 'print_id': 134274}, {'counts': 1, 'layout_z': 17.392635113631542, 'model_weight': 5.297, 'order_id': 927128, 'pid': 390373, 'print_id': 134275}, {'counts': 1, 'layout_z': 26.139986312446986, 'model_weight': 15.312, 'order_id': 927129, 'pid': 390375, 'print_id': 134276}, {'counts': 1, 'layout_z': 17.491576609126483, 'model_weight': 6.495, 'order_id': 927130, 'pid': 390376, 'print_id': 134277}, {'counts': 1, 'layout_z': 15.57976295844962, 'model_weight': 5.443, 'order_id': 927131, 'pid': 390377, 'print_id': 134278}, {'counts': 1, 'layout_z': 16.006999969482422, 'model_weight': 4.683, 'order_id': 927132, 'pid': 390378, 'print_id': 134279}, {'counts': 1, 'layout_z': 18.770485206437296, 'model_weight': 6.114, 'order_id': 927137, 'pid': 390383, 'print_id': 134280}, {'counts': 1, 'layout_z': 21.480148458997267, 'model_weight': 9.586, 'order_id': 927133, 'pid': 390379, 'Line truncated
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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, 'print_id': 134185}, {'counts': 1, 'layout_z': 46.23669371110479, 'model_weight': 56.196, 'order_id': 926778, 'pid': 389918, 'print_id': 134186}, {'counts': 1, 'layout_z': 24.822566986083984, 'model_weight': 31.522, 'order_id': 926268, 'pid': 389067, 'print_id': 134211}, {'counts': 1, 'layout_z': 25.085425667575343, 'model_weight': 31.077, 'order_id': 926267, 'pid': 389066, 'print_id': 134212}, {'counts': 1, 'layout_z': 18.154759649173364, 'model_weight': 6.256, 'order_id': 927059, 'pid': 390269, 'print_id': 134216}, {'counts': 1, 'layout_z': 24.2420189021486, 'model_weight': 14.472, 'order_id': 927065, 'pid': 390275, 'print_id': 134220}, {'counts': 1, 'layout_z': 16.757099114319693, 'model_weight': 5.335, 'order_id': 927078, 'pid': 390299, 'print_id': 134226}, {'counts': 1, 'layout_z': 18.796780948141503, 'model_weight': 7.295, 'order_id': 927079, 'pid': 390300, 'print_id': 134228}, {'counts': 1, 'layout_z': 17.920740666248633, 'model_weight': 7.869, 'order_id': 927082, 'pid': 390303, 'print_id': 134229}, {'counts': 1, 'layout_z': 16.320665859825066, 'model_weight': 4.73, 'order_id': 927081, 'pid': 390302, 'print_id': 134230}, {'counts': 1, 'layout_z': 23.250497020255544, 'model_weight': 15.567, 'order_id': 927100, 'pid': 390331, 'print_id': 134242}, {'counts': 1, 'layout_z': 26.276874511435977, 'model_weight': 19.813, 'order_id': 927103, 'pid': 390334, 'print_id': 134246}, {'counts': 1, 'layout_z': 17.08049576865031, 'model_weight': 5.858, 'order_id': 927111, 'pid': 390342, 'print_id': 134254}, {'counts': 1, 'layout_z': 19.196685578562278, 'model_weight': 6.465, 'order_id': 927117, 'pid': 390347, 'print_id': 134261}, {'counts': 1, 'layout_z': 26.507062216602122, 'model_weight': 14.287, 'order_id': 927116, 'pid': 390346, 'print_id': 134262}, {'counts': 1, 'layout_z': 16.440782827635232, 'model_weight': 5.493, 'order_id': 927118, 'pid': 390348, 'print_id': 134263}, {'counts': 1, 'layout_z': 41.42868301509347, 'model_weight': 68.274, 'order_id': 927122, 'pid': 390354, 'print_id': 134264}, {'counts': 1, 'layout_z': 15.705368176518945, 'model_weight': 4.423, 'order_id': 927119, 'pid': 390349, 'print_id': 134265}, {'counts': 1, 'layout_z': 16.363223697461702, 'model_weight': 5.634, 'order_id': 927120, 'pid': 390351, 'print_id': 134266}, {'counts': 1, 'layout_z': 24.653417686230497, 'model_weight': 17.851, 'order_id': 927121, 'pid': 390353, 'print_id': 134267}, {'counts': 1, 'layout_z': 24.327745611835496, 'model_weight': 28.23, 'order_id': 926040, 'pid': 388832, 'print_id': 134268}, {'counts': 1, 'layout_z': 27.301779030909188, 'model_weight': 23.926, 'order_id': 923281, 'pid': 385001, 'print_id': 134269}, {'counts': 1, 'layout_z': 25.869120288866796, 'model_weight': 32.329, 'order_id': 926077, 'pid': 388864, 'print_id': 134270}, {'counts': 1, 'layout_z': 36.37214874852985, 'model_weight': 65.744, 'order_id': 926086, 'pid': 388873, 'print_id': 134271}, {'counts': 1, 'layout_z': 37.44403689090713, 'model_weight': 80.67, 'order_id': 926097, 'pid': 388884, 'print_id': 134273}, {'counts': 1, 'layout_z': 27.890566642299536, 'model_weight': 22.715, 'order_id': 927127, 'pid': 390372, 'print_id': 134274}, {'counts': 1, 'layout_z': 17.392635113631542, 'model_weight': 5.297, 'order_id': 927128, 'pid': 390373, 'print_id': 134275}, {'counts': 1, 'layout_z': 26.139986312446986, 'model_weight': 15.312, 'order_id': 927129, 'pid': 390375, 'print_id': 134276}, {'counts': 1, 'layout_z': 17.491576609126483, 'model_weight': 6.495, 'order_id': 927130, 'pid': 390376, 'print_id': 134277}, {'counts': 1, 'layout_z': 15.57976295844962, 'model_weight': 5.443, 'order_id': 927131, 'pid': 390377, 'print_id': 134278}, {'counts': 1, 'layout_z': 16.006999969482422, 'model_weight': 4.683, 'order_id': 927132, 'pid': 390378, 'print_id': 134279}, {'counts': 1, 'layout_z': 18.770485206437296, 'model_weight': 6.114, 'order_id': 927137, 'pid': 390383, 'print_id': 134280}, {'counts': 1, 'layout_z': 21.480148458997267, 'model_weight': 9.586, 'order_id': 927133, 'pid': 390379,Line truncated
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test_print_max = 80
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# -------------------------- 结束：测试相关 -------------------------------
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+3
-9
@@ -16,6 +16,7 @@ import argparse
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from config import print_factory_type_dir
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from config import oss_config
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from config import print_data_dir
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from config import url_get_oss_suffix_by_orderId
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from general import is_use_debug_oss
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from general import transform_save_o3d
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@@ -1291,19 +1292,13 @@ def read_pids_from_json(pid_file):
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return list_model_info, data
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def download_data_by_json(model_info, workdir, oss_client ):
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'''
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下载卡通化数据
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'''
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try:
|
||||
pid = model_info.pid
|
||||
model_height = model_info.model_height
|
||||
# target_dir = f"{workdir}/{pid}_image"
|
||||
target_dir = f"{workdir}"
|
||||
|
||||
# {"code":1000,"data":"base_cartoon/badge/101/3/init_obj","message":"success1"}
|
||||
# https://mp.api.suwa3d.com/api/order/getOssSuffixByOrderId?order_id=879312
|
||||
|
||||
url = f"https://mp.api.suwa3d.com/api/order/getOssSuffixByOrderId?order_id={model_info.order_id}"
|
||||
url = f"{url_get_oss_suffix_by_orderId}{model_info.order_id}"
|
||||
res = requests.get(url)
|
||||
|
||||
data = res.json()["data"]
|
||||
@@ -1334,7 +1329,6 @@ 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)
|
||||
|
||||
|
||||
@@ -13,6 +13,8 @@ import requests
|
||||
import json
|
||||
import shutil
|
||||
|
||||
from config import url_get_oss_suffix_by_orderId
|
||||
|
||||
def download_transform_save_by_json(pid_file, workdir, oss_config):
|
||||
layout_data = download_datas_by_json(pid_file, workdir, oss_config)
|
||||
original_obj_pid_dir = workdir
|
||||
@@ -221,7 +223,7 @@ def download_data_by_json(model_info, workdir, oss_client ):
|
||||
model_height = model_info.model_height
|
||||
target_dir = f"{workdir}"
|
||||
|
||||
url = f"https://mp.api.suwa3d.com/api/order/getOssSuffixByOrderId?order_id={model_info.order_id}"
|
||||
url = f"{url_get_oss_suffix_by_orderId}{model_info.order_id}"
|
||||
res = requests.get(url)
|
||||
|
||||
data = res.json()["data"]
|
||||
|
||||
+1
-1
@@ -258,7 +258,7 @@ def is_same_obj(obj_name1, obj_name2):
|
||||
pre_name1 = obj_name1.split("_x")[0]
|
||||
pre_name2 = obj_name2.split("_x")[0]
|
||||
|
||||
print(f"pre_name1={pre_name1}, pre_name2={pre_name2}")
|
||||
# print(f"pre_name1={pre_name1}, pre_name2={pre_name2}")
|
||||
|
||||
if (pre_name1==pre_name2):
|
||||
return True
|
||||
|
||||
+1
-368
@@ -9,18 +9,12 @@ import open3d as o3d
|
||||
import numpy as np
|
||||
from plyfile import PlyData, PlyElement
|
||||
|
||||
from config import print_factory_type_dir
|
||||
|
||||
from general import mesh_tranform_to_pcd
|
||||
from general import need_upload_result
|
||||
from general import read_mesh
|
||||
|
||||
from compute_print_net import get_models_bbox
|
||||
from compute_print_net import arrange_models_on_platform
|
||||
from compute_print_net import Platform
|
||||
from compute_print_net import down_sample
|
||||
from compute_print_net import compute_bbox_all
|
||||
from compute_print_net import compute_bbox_all_ext
|
||||
|
||||
def make_bbox_for_print(base_original_obj_dir,dict_bad,dict_origin,is_downsample):
|
||||
"""获取需要的盒子大小"""
|
||||
@@ -87,7 +81,6 @@ def get_pcd_by_matrix(dict_mesh_obj,dict_total_matrix,dict_ply_name):
|
||||
|
||||
return dict_pcd_fix
|
||||
|
||||
|
||||
def ply_print_layout_platform(dict_pcd_fix,dict_pcd_fix2,machine_size,dict_total_matrix,all_models):
|
||||
"""根据排版结果移动点云到指定位置"""
|
||||
# placed_models,unplaced_models = get_models_box_size(dict_fix,machine_size)
|
||||
@@ -144,32 +137,6 @@ def ply_print_layout_platform(dict_pcd_fix,dict_pcd_fix2,machine_size,dict_total
|
||||
|
||||
return placed_models
|
||||
|
||||
def get_models_bbox_net(dict_pcd_fix):
|
||||
return get_models_bbox(dict_pcd_fix)
|
||||
|
||||
"""
|
||||
def get_models_box_size(dict_fix,machine_size):
|
||||
#获取排版的盒子大小
|
||||
models = []
|
||||
for ply_file in dict_fix:
|
||||
bbox_with_text = ply_file.split("=")
|
||||
bbox_with = bbox_with_text[-1]
|
||||
split_text = bbox_with.replace(".ply","").split("+")
|
||||
extend_dist = 2
|
||||
x_length = int(float(split_text[2])*100) + extend_dist
|
||||
y_length = int(float(split_text[0])*100) + extend_dist
|
||||
z_length = int(float(split_text[1])*100) + extend_dist
|
||||
#print("get_models_box_size",x_length,y_length,z_length)
|
||||
models.append({'name':ply_file,'dimensions':(int(x_length/100),int(z_length/100),int(y_length/100))})
|
||||
print(models)
|
||||
|
||||
platform = Platform(int(machine_size[0]), int(machine_size[1]), int(machine_size[2]))
|
||||
print("开始计算排序...")
|
||||
platform.arrange_models(models)
|
||||
platform.print_results()
|
||||
return platform.get_result()
|
||||
"""
|
||||
|
||||
def compute_distance(pcd1, pcd2):
|
||||
"""
|
||||
正确计算两个点云之间距离的函数。
|
||||
@@ -187,44 +154,6 @@ def compute_distance(pcd1, pcd2):
|
||||
# return min_dist, mean_dist, distances
|
||||
return min_dist
|
||||
|
||||
def compute_distance_x(pcd1, pcd2):
|
||||
points1 = np.asarray(pcd1.points)[:, 0] # 提取所有X坐标[3](@ref)
|
||||
points2 = np.asarray(pcd2.points)[:, 0]
|
||||
|
||||
x_diff = np.abs(points1[:, np.newaxis] - points2)
|
||||
return np.min(x_diff)
|
||||
|
||||
def compute_distance_y(pcd1, pcd2):
|
||||
points1 = np.asarray(pcd1.points)[:, 1] # 提取所有Y坐标[3](@ref)
|
||||
points2 = np.asarray(pcd2.points)[:, 1]
|
||||
|
||||
y_diff = np.abs(points1.reshape(-1, 1) - points2)
|
||||
return np.min(y_diff)
|
||||
|
||||
def check_collision_x(pcd_moving, static_pcds,collision_threshold):
|
||||
moving_points = np.asarray(pcd_moving.points)
|
||||
min_distance_to_x_axis = np.min(np.abs(moving_points[:, 1])) # Y 坐标即为与 X 轴的距离
|
||||
#print(f"与 X 轴的最小距离: {min_distance_to_x_axis}")
|
||||
#print(f"与 Y 轴的最小距离: {min_distance_to_y_axis}")
|
||||
#print(f"pcd_moving{len(static_pcds)}")
|
||||
if min_distance_to_x_axis < collision_threshold:
|
||||
print(f"与 X 轴发生碰撞! 最小距离: {min_distance_to_x_axis}")
|
||||
return True
|
||||
|
||||
return check_collision_all(pcd_moving, static_pcds,collision_threshold)
|
||||
|
||||
def check_collision_y(pcd_moving, static_pcds,collision_threshold):
|
||||
moving_points = np.asarray(pcd_moving.points)
|
||||
#print(f"与 X 轴的最小距离: {min_distance_to_x_axis}")
|
||||
min_distance_to_y_axis = np.min(np.abs(moving_points[:, 0])) # X 坐标即为与 Y 轴的距离
|
||||
#print(f"与 Y 轴的最小距离: {min_distance_to_y_axis}")
|
||||
#print(f"pcd_moving{len(static_pcds)}")
|
||||
if min_distance_to_y_axis < collision_threshold:
|
||||
print(f"与 Y 轴发生碰撞! 最小距离: {min_distance_to_y_axis}")
|
||||
return True
|
||||
|
||||
return check_collision_all(pcd_moving, static_pcds,collision_threshold)
|
||||
|
||||
import numpy as np
|
||||
|
||||
def compute_aabb(pcd):
|
||||
@@ -349,9 +278,6 @@ def compact_mode_for_min_dis_json(placed_models,dict_unplaced,dict_bounds_fix,ma
|
||||
else:
|
||||
pcd_second.append(pcd)
|
||||
|
||||
# pcd_all.append(pcd_downsampled)
|
||||
# name_list.append(model['name'])
|
||||
# model_list.append(model)
|
||||
dict_name[pcd] = model['name']
|
||||
dict_model[pcd] = model
|
||||
dx = model['dimensions'][0]
|
||||
@@ -374,7 +300,6 @@ def compact_mode_for_min_dis_json(placed_models,dict_unplaced,dict_bounds_fix,ma
|
||||
if max_delta_x < 10:
|
||||
draw_down = False
|
||||
|
||||
# for idx, pcd in enumerate(pcd_all):
|
||||
for idx, pcd in enumerate(pcd_first):
|
||||
|
||||
if dict_model[pcd]['first_line']:
|
||||
@@ -1001,15 +926,6 @@ def compact_mode_for_min_dis_json(placed_models,dict_unplaced,dict_bounds_fix,ma
|
||||
#"""
|
||||
|
||||
last_pcd_processed.append(pcd)
|
||||
"""
|
||||
print("is_x_top",is_x_top)
|
||||
if not is_x_top:
|
||||
last_pcd_processed.append(pcd)
|
||||
print("last_pcd_processed.append",name)
|
||||
else:
|
||||
print("fail last_pcd_processed.append",name, is_x_top)
|
||||
"""
|
||||
# o3d.io.write_point_cloud(os.path.join(output_dir, name), pcd)
|
||||
|
||||
dict_total_matrix[obj_name]= T_trans1 @ dict_total_matrix[obj_name]
|
||||
|
||||
@@ -1029,19 +945,6 @@ def move_to_top_left(pcd, edge_x_min, edge_y_max):
|
||||
|
||||
return T_transTemp
|
||||
|
||||
def move_to_bottom_left(pcd, edge_x_min, edge_y_min):
|
||||
|
||||
points = np.asarray(pcd.points)
|
||||
min_x = np.min(points[:, 0])
|
||||
min_y = np.min(points[:, 1])
|
||||
tx = edge_x_min - min_x
|
||||
ty = edge_y_min - min_y
|
||||
pcd.translate((tx, ty, 0), relative=True)
|
||||
T_transTemp = np.eye(4)
|
||||
T_transTemp[:3, 3] = [tx, ty, 0]
|
||||
|
||||
return T_transTemp
|
||||
|
||||
def move_to_bottom_right(pcd, edge_x_max, edge_y_min):
|
||||
|
||||
points = np.asarray(pcd.points)
|
||||
@@ -1066,229 +969,8 @@ def get_axis_aligned_bbox(pcd):
|
||||
'z_max': np.max(points[:,2])
|
||||
}
|
||||
|
||||
def down_obj_data_to_ply(weight_fix_out_obj_dir,weight_fix_out_ply_dir):
|
||||
""""""
|
||||
obj_file_list = [aa for aa in os.listdir(weight_fix_out_obj_dir) if aa.endswith(".obj")]
|
||||
for obj_name in obj_file_list:
|
||||
obj_path = os.path.join(weight_fix_out_obj_dir,obj_name)
|
||||
|
||||
mesh_obj = read_mesh(obj_path)
|
||||
|
||||
vertices = np.asarray(mesh_obj.vertices)
|
||||
pcd = o3d.geometry.PointCloud()
|
||||
pcd.points = o3d.utility.Vector3dVector(vertices)
|
||||
voxel_size = 3 # 设置体素的大小，决定下采样的密度
|
||||
pcd_downsampled = down_sample(pcd, voxel_size)
|
||||
ply_out_path = os.path.join(weight_fix_out_ply_dir,obj_name.replace(".obj",".ply"))
|
||||
o3d.io.write_point_cloud(ply_out_path, pcd_downsampled)
|
||||
print(ply_out_path,"下采样完成。")
|
||||
|
||||
def compute_centroid_compact(pcd):
|
||||
points = np.asarray(pcd.points)
|
||||
centroid = np.mean(points, axis=0)
|
||||
return centroid
|
||||
|
||||
def compute_base_point(pcd):
|
||||
points = np.asarray(pcd.points)
|
||||
x_center = np.mean(points[:, 0])
|
||||
y_center = np.mean(points[:, 1])
|
||||
min_z = np.min(points[:, 2])
|
||||
return np.array([x_center, y_center, min_z])
|
||||
|
||||
import copy
|
||||
def move_obj_to_compact_bounds(bounds_fix_out_dir,bounds_compact_out_dir,weight_fix_out_obj_dir,base_original_obj_dir,compact_obj_out_dir,dict_mesh_obj,dict_unplaced,placed_remove_dir,dict_bad,bad_dir,full_dir,dict_bounds_fix,dict_compact,dict_origin):
|
||||
""""""
|
||||
# obj_file_list = [aa for aa in os.listdir(weight_fix_out_obj_dir) if aa.endswith(".obj")]
|
||||
obj_file_list = list(dict_mesh_obj.keys())
|
||||
ply_path_dict = {}
|
||||
|
||||
# meshes = []
|
||||
# for ply_file_name in os.listdir(bounds_fix_out_dir):
|
||||
for ply_file_name in dict_bounds_fix:
|
||||
ply_dict_key = ply_file_name.split("=")[0]
|
||||
ply_path_dict[ply_dict_key] = ply_file_name
|
||||
for obj_name in obj_file_list:
|
||||
obj_path = os.path.join(weight_fix_out_obj_dir, obj_name)
|
||||
|
||||
# mesh_obj = read_mesh(obj_path, False)
|
||||
mesh_obj = dict_mesh_obj[obj_name]
|
||||
# mesh_obj = dict_origin[obj_origin_path]
|
||||
|
||||
original_obj_pid_dir = base_original_obj_dir
|
||||
obj_origin_path = os.path.join(original_obj_pid_dir, obj_name)
|
||||
obj_origin = dict_origin[obj_origin_path]
|
||||
# obj_origin = copy.deepcopy(dict_origin[obj_origin_path])
|
||||
|
||||
ply_name_pid = obj_name.replace(".obj","")
|
||||
# ply_name = ply_path_dict[ply_name_pid]
|
||||
ply_name = ply_path_dict.get(ply_name_pid,None)
|
||||
print(ply_name_pid,ply_name)
|
||||
if ply_name is None:
|
||||
continue
|
||||
print("move_obj_to_compact_bounds",ply_name,len(dict_unplaced))
|
||||
if not ply_name or ply_name in dict_unplaced:
|
||||
print("unplaced",ply_name)
|
||||
continue
|
||||
ply_fix_path = os.path.join(bounds_fix_out_dir,ply_name)
|
||||
ply_compact_path = os.path.join(bounds_compact_out_dir, ply_name)
|
||||
# pcd_fix = o3d.io.read_point_cloud(ply_fix_path)
|
||||
pcd_fix = dict_bounds_fix[ply_name]
|
||||
|
||||
vertices = np.asarray(obj_origin.vertices)
|
||||
pcd_origin = o3d.geometry.PointCloud()
|
||||
pcd_origin.points = o3d.utility.Vector3dVector(vertices)
|
||||
|
||||
# pcd_compact = o3d.io.read_point_cloud(ply_compact_path)
|
||||
pcd_compact = dict_compact[ply_name]
|
||||
|
||||
centroid_fix = compute_centroid_compact(pcd_fix)
|
||||
centroid_compact = compute_centroid_compact(pcd_compact)
|
||||
centroid_origin = compute_centroid_compact(pcd_origin)
|
||||
displacement = centroid_compact - centroid_fix
|
||||
# displacement = centroid_compact - centroid_origin
|
||||
vertices = np.asarray(mesh_obj.vertices)
|
||||
vertices_translated = vertices + displacement # 将位移应用到每个顶点
|
||||
mesh_obj.vertices = o3d.utility.Vector3dVector(vertices_translated) # 更新网格顶点
|
||||
|
||||
obj_pid = obj_name.split("_P")[0]
|
||||
#compact_obj_pid_out_dir = os.path.join(compact_obj_out_dir,obj_pid)
|
||||
compact_obj_pid_out_dir= compact_obj_out_dir
|
||||
if not os.path.exists(compact_obj_pid_out_dir):
|
||||
os.makedirs(compact_obj_pid_out_dir)
|
||||
obj_path_compact = os.path.join(compact_obj_pid_out_dir,obj_name)
|
||||
mesh_obj.compute_vertex_normals()
|
||||
o3d.io.write_triangle_mesh(obj_path_compact, mesh_obj,write_triangle_uvs=True)
|
||||
print(obj_path_compact, "移动后obj保存完成", displacement)
|
||||
|
||||
# meshes.append(mesh_obj)
|
||||
|
||||
#original_obj_pid_dir = os.path.join(base_original_obj_dir,obj_pid)
|
||||
original_obj_pid_dir = base_original_obj_dir
|
||||
for mtl in os.listdir(compact_obj_pid_out_dir):
|
||||
if mtl.endswith(".mtl"):
|
||||
if obj_pid in mtl:
|
||||
mtl_path = os.path.join(compact_obj_pid_out_dir,mtl)
|
||||
os.remove(mtl_path)
|
||||
|
||||
mtl_name = None
|
||||
tex_name = None
|
||||
for file_name in os.listdir(original_obj_pid_dir):
|
||||
if file_name.endswith(".mtl"):
|
||||
if obj_pid in file_name:
|
||||
mtl_name = file_name
|
||||
if file_name.endswith(".jpg"):
|
||||
if obj_pid in file_name:
|
||||
tex_name = file_name
|
||||
if file_name.endswith(".png"):
|
||||
if obj_pid in file_name:
|
||||
tex_name = file_name
|
||||
|
||||
for file in os.listdir(original_obj_pid_dir):
|
||||
#print(f"file{file}")
|
||||
if file.endswith(".obj"):
|
||||
continue
|
||||
if obj_pid not in file:
|
||||
continue
|
||||
|
||||
origin_path = os.path.join(original_obj_pid_dir,file)
|
||||
dis_path = os.path.join(compact_obj_pid_out_dir,file)
|
||||
|
||||
if os.path.isfile(origin_path):
|
||||
#print(f'origin_path{origin_path}')
|
||||
#print(f'dis_path{dis_path}')
|
||||
shutil.copy(origin_path,dis_path)
|
||||
time.sleep(1)
|
||||
#print("-"*50)
|
||||
base_origin_obj_path = os.path.join(original_obj_pid_dir,obj_name)
|
||||
#print(f"base_origin_obj_path{base_origin_obj_path}")
|
||||
#print(f"obj_path_compact{obj_path_compact}")
|
||||
update_obj_file(base_origin_obj_path, obj_path_compact)
|
||||
|
||||
placed_remove_obj_path = os.path.join(placed_remove_dir, obj_name)
|
||||
shutil.copy(base_origin_obj_path,placed_remove_obj_path)
|
||||
os.remove(base_origin_obj_path)
|
||||
|
||||
exist_obj_any = False
|
||||
exist_obj = False
|
||||
delete_mtl = False
|
||||
for file_name in os.listdir(original_obj_pid_dir):
|
||||
if file_name.endswith(".obj"):
|
||||
if obj_pid in file_name:
|
||||
exist_obj = True
|
||||
exist_obj_any = True
|
||||
|
||||
if not exist_obj_any:
|
||||
delete_mtl = True
|
||||
if not exist_obj:
|
||||
delete_mtl = True
|
||||
|
||||
if delete_mtl:
|
||||
print("delete_mtl",mtl_name,tex_name)
|
||||
if mtl_name!=None:
|
||||
base_origin_mtl_path = os.path.join(original_obj_pid_dir,mtl_name)
|
||||
placed_remove_mtl_path = os.path.join(placed_remove_dir, mtl_name)
|
||||
shutil.copy(base_origin_mtl_path,placed_remove_mtl_path)
|
||||
os.remove(base_origin_mtl_path)
|
||||
|
||||
if tex_name!=None:
|
||||
base_origin_tex_path = os.path.join(original_obj_pid_dir,tex_name)
|
||||
placed_remove_tex_path = os.path.join(placed_remove_dir, tex_name)
|
||||
shutil.copy(base_origin_tex_path,placed_remove_tex_path)
|
||||
os.remove(base_origin_tex_path)
|
||||
|
||||
print(f"排版错误模型数量：：{len(dict_bad)}")
|
||||
for obj_name in dict_bad:
|
||||
print("--错误模型名：", obj_name)
|
||||
process_obj_files(original_obj_pid_dir,bad_dir,obj_name)
|
||||
|
||||
print(f"排版剩余模型数量：：{len(dict_unplaced)}")
|
||||
for ply_file_name in dict_unplaced:
|
||||
obj_name = ply_file_name.split("=")[0]+".obj"
|
||||
print("--剩余模型名：", obj_name)
|
||||
process_obj_files(original_obj_pid_dir,full_dir,obj_name)
|
||||
|
||||
import json
|
||||
|
||||
def extract_angles(R):
|
||||
# 提取绕X、Y、Z轴的旋转角度（弧度）
|
||||
rx_rad = np.arctan2(R[2, 1], R[2, 2]) # X轴旋转
|
||||
ry_rad = np.arcsin(-R[2, 0]) # Y轴旋转
|
||||
rz_rad = np.arctan2(R[1, 0], R[0, 0]) # Z轴旋转
|
||||
|
||||
# 将弧度转换为角度（度数）
|
||||
rx_deg = np.degrees(rx_rad)
|
||||
ry_deg = np.degrees(ry_rad)
|
||||
rz_deg = np.degrees(rz_rad)
|
||||
|
||||
return rx_deg, ry_deg, rz_deg
|
||||
|
||||
def compute_mesh_center(vertices):
|
||||
"""
|
||||
计算网格质心
|
||||
|
||||
参数:
|
||||
vertices: 顶点坐标数组，形状为(N, 3)的NumPy数组或列表
|
||||
|
||||
返回:
|
||||
centroid: 质心坐标的NumPy数组 [x, y, z]
|
||||
"""
|
||||
if len(vertices) == 0:
|
||||
raise ValueError("顶点数组不能为空")
|
||||
|
||||
n = len(vertices) # 顶点数量
|
||||
# 初始化坐标累加器
|
||||
sum_x, sum_y, sum_z = 0.0, 0.0, 0.0
|
||||
|
||||
# 遍历所有顶点累加坐标值
|
||||
for vertex in vertices:
|
||||
sum_x += vertex[0]
|
||||
sum_y += vertex[1]
|
||||
sum_z += vertex[2]
|
||||
|
||||
# 计算各坐标轴的平均值
|
||||
centroid = np.array([sum_x / n, sum_y / n, sum_z / n])
|
||||
return centroid
|
||||
|
||||
import re
|
||||
def extract_numbers_from_filename(filename):
|
||||
"""
|
||||
@@ -1313,7 +995,7 @@ def extract_numbers_from_filename(filename):
|
||||
|
||||
import requests
|
||||
def move_obj_to_compact_bounds_json(base_original_obj_dir,dict_mesh_obj,dict_unplaced,dict_bad,bad_dir,full_dir,dict_bounds_fix,
|
||||
dict_total_matrix,save_mesh,batch_id, print_start_time,selected_machine,selected_mode,version):
|
||||
dict_total_matrix,batch_id, print_start_time,selected_machine,selected_mode,version):
|
||||
"""生成3D打印布局的JSON数据并保存为3DPrintLayout.json"""
|
||||
# 创建符合3DPrintLayout规范的JSON数据结构
|
||||
layout_data = {
|
||||
@@ -1429,10 +1111,6 @@ def move_obj_to_compact_bounds_json(base_original_obj_dir,dict_mesh_obj,dict_unp
|
||||
print("--剩余模型名：", obj_name)
|
||||
process_obj_files(original_obj_pid_dir,full_dir,obj_name)
|
||||
|
||||
if save_mesh:
|
||||
cache_type_setting_dir=f"{base_original_obj_dir}/arrange"
|
||||
transform_save_o3d(layout_data, original_obj_pid_dir, cache_type_setting_dir)
|
||||
|
||||
return send_layout_data
|
||||
|
||||
def process_obj_files(original_obj_pid_dir,placed_remove_dir,obj_name):
|
||||
@@ -1494,31 +1172,6 @@ def process_obj_files(original_obj_pid_dir,placed_remove_dir,obj_name):
|
||||
shutil.copy(base_origin_tex_path, placed_remove_tex_path)
|
||||
os.remove(base_origin_tex_path)
|
||||
|
||||
def update_obj_file(original_obj_path,compact_obj_path):
|
||||
""""""
|
||||
with open(original_obj_path, "r") as f:
|
||||
lines_original = f.readlines()
|
||||
mtllib_name = None
|
||||
mat_name = None
|
||||
for line in lines_original:
|
||||
if line.startswith("mtllib"):
|
||||
mtllib_name = line.split(" ")[1]
|
||||
elif line.startswith("usemtl"):
|
||||
mat_name = line.split(" ")[1]
|
||||
if mtllib_name and mat_name:
|
||||
break
|
||||
with open(compact_obj_path, "r") as f:
|
||||
lines = f.readlines()
|
||||
new_lines = []
|
||||
for line2 in lines:
|
||||
if line2.startswith("mtllib"):
|
||||
line2 = f"mtllib {mtllib_name}\n" # 替换为原始 MTL 文件路径
|
||||
elif line2.startswith("usemtl"):
|
||||
line2 = f"usemtl {mat_name}\n" # 替换为原始贴图路径
|
||||
new_lines.append(line2)
|
||||
with open(compact_obj_path, "w") as f:
|
||||
f.writelines(new_lines)
|
||||
|
||||
def pass_for_min_dis(placed_models, dict_unplaced, dict_bounds_fix):
|
||||
|
||||
pcd_all = []
|
||||
@@ -1546,23 +1199,3 @@ def pass_for_min_dis(placed_models, dict_unplaced, dict_bounds_fix):
|
||||
name = name_list[idx]
|
||||
print("fail to place (x=0)", name_list[idx], y, dy)
|
||||
dict_unplaced[name]=name
|
||||
|
||||
if __name__ == '__main__':
|
||||
out_dir = "/data/datasets_20t/type_setting_test_data/"
|
||||
weight_fix_out_obj_dir = f"{out_dir}/print_weight_fix_data_obj"
|
||||
weight_fix_out_ply_dir = f"{out_dir}/data/datasets_20t/type_ssetting_test_data/print_weight_fix_data_ply"
|
||||
|
||||
base_original_obj_dir=f"{print_factory_type_dir}/8/"
|
||||
if not os.path.exists(weight_fix_out_ply_dir):
|
||||
os.makedirs(weight_fix_out_ply_dir)
|
||||
bounds_fix_out_dir = f"{out_dir}/print_bounds_fix_data"
|
||||
bounds_compact_out_dir = f"{out_dir}/print_bounds_compact_data"
|
||||
compact_obj_out_dir = f"{out_dir}//print_compact_obj"
|
||||
if not os.path.exists(bounds_fix_out_dir):
|
||||
os.mkdir(bounds_fix_out_dir)
|
||||
if not os.path.exists(bounds_compact_out_dir):
|
||||
os.makedirs(bounds_compact_out_dir)
|
||||
if not os.path.exists(compact_obj_out_dir):
|
||||
os.makedirs(compact_obj_out_dir)
|
||||
|
||||
move_obj_to_compact_bounds(bounds_fix_out_dir,bounds_compact_out_dir,weight_fix_out_obj_dir,base_original_obj_dir,compact_obj_out_dir)
|
||||
@@ -13,6 +13,7 @@ from test_load_json import load_show_save
|
||||
from download_print import upload_result
|
||||
|
||||
from config import print_factory_type_dir
|
||||
from config import print_data_dir
|
||||
from config import url_send_layout
|
||||
from config import big_machine_size
|
||||
from config import small_machine_size
|
||||
@@ -101,12 +102,11 @@ def print_type_setting_obj(base_original_obj_dir=None,batch_id=0,selected_mode="
|
||||
os.makedirs(full_dir)
|
||||
|
||||
is_small_machine = True if selected_machine=="小机型" else False
|
||||
save_mesh = True if output_format=="模型" else False
|
||||
|
||||
version = "print_type_setting25.local"
|
||||
|
||||
send_layout_data = move_obj_to_compact_bounds_json(base_original_obj_dir,dict_mesh_obj,dict_unplaced,dict_bad,bad_dir,full_dir,dict_pcd_fix,
|
||||
dict_total_matrix,save_mesh,batch_id,print_start_time,selected_machine,selected_mode,version)
|
||||
dict_total_matrix,batch_id,print_start_time,selected_machine,selected_mode,version)
|
||||
|
||||
end_time4 = time.time()
|
||||
print("排版完成")
|
||||
@@ -151,7 +151,6 @@ def print_type_setting_obj(base_original_obj_dir=None,batch_id=0,selected_mode="
|
||||
print(f"need_upload_result={need_upload_result()}")
|
||||
if need_upload_result():
|
||||
print(f"send_layout_data={send_layout_data}")
|
||||
# url = 'https://mp.api.suwa3d.com/api/printTypeSettingOrder/printTypeSettingOrderSuccess'
|
||||
url = url_send_layout
|
||||
try:
|
||||
response = requests.post(url, json.dumps(send_layout_data), timeout=30)
|
||||
@@ -180,35 +179,19 @@ def print_type_setting_obj(base_original_obj_dir=None,batch_id=0,selected_mode="
|
||||
|
||||
return 0
|
||||
|
||||
def preview(base_original_obj_dir=None, batch_id=0):
|
||||
|
||||
load_show_save(base_original_obj_dir, {}, batch_id, True)
|
||||
|
||||
def get_pcd(obj, is_down_sample=True):
|
||||
vertices = np.asarray(obj.vertices)
|
||||
pcd = o3d.geometry.PointCloud()
|
||||
pcd.points = o3d.utility.Vector3dVector(vertices)
|
||||
|
||||
if is_down_sample:
|
||||
voxel_size = 3
|
||||
pcd_downsampled = down_sample(pcd, voxel_size, False)
|
||||
return pcd_downsampled
|
||||
else:
|
||||
return pcd
|
||||
|
||||
if __name__ == '__main__':
|
||||
# parser = argparse.ArgumentParser()
|
||||
# parser.add_argument("--batch_id", type=str, required=True, help="batch_id")
|
||||
# args = parser.parse_args()
|
||||
|
||||
# batch_id = args.batch_id
|
||||
batch_id = "9910032"
|
||||
batch_id = "1"
|
||||
src_dir = batch_id
|
||||
selected_mode="紧凑" # 标准 紧凑
|
||||
output_format="JSON" # 模型 JSON
|
||||
selected_machine = "大机型" # 小机型 大机型
|
||||
|
||||
base_original_obj_dir = f"{print_factory_type_dir}/{src_dir}"
|
||||
base_original_obj_dir = f"{print_data_dir}/{src_dir}"
|
||||
|
||||
print_type_setting_obj(base_original_obj_dir=base_original_obj_dir,
|
||||
batch_id=batch_id,selected_mode=selected_mode,output_format=output_format,selected_machine=selected_machine)
|
||||
+5
-7
@@ -6,8 +6,8 @@ from PIL import Image
|
||||
import argparse
|
||||
import gc
|
||||
|
||||
from config import print_factory_type_dir
|
||||
from config import print_data_dir
|
||||
from config import test_print_max
|
||||
|
||||
from general import mesh_transform_by_matrix
|
||||
from general import read_mesh
|
||||
@@ -96,8 +96,9 @@ def load_and_transform_models(base_path, dict_origin, json_name):
|
||||
print(f"已加载并变换: {index} {os.path.basename(obj_path)}")
|
||||
index = index + 1
|
||||
|
||||
# if (index > 80):
|
||||
# break
|
||||
if test_print_max > 0:
|
||||
if (index > test_print_max):
|
||||
break
|
||||
|
||||
add_plank = True
|
||||
if add_plank:
|
||||
@@ -356,7 +357,7 @@ def set_orthographic(meshes, width=1920, height=1080,
|
||||
del mesh
|
||||
del points
|
||||
gc.collect()
|
||||
print(f"set_orthographic {index}")
|
||||
# print(f"set_orthographic {index}")
|
||||
index = index + 1
|
||||
|
||||
del meshes
|
||||
@@ -405,7 +406,6 @@ def set_orthographic(meshes, width=1920, height=1080,
|
||||
view_control.set_up([0, 1, 0])
|
||||
ortho_width = ortho_width or 10.0
|
||||
|
||||
print("set_orthographic 1")
|
||||
#for _ in range(2):
|
||||
# vis.poll_events()
|
||||
# vis.update_renderer()
|
||||
@@ -413,10 +413,8 @@ def set_orthographic(meshes, width=1920, height=1080,
|
||||
# 设置正交投影
|
||||
try:
|
||||
set_orthographic_camera(view_control)
|
||||
print("set_orthographic 2")
|
||||
except AttributeError:
|
||||
set_orthographic_projection(view_control, ortho_scale=15.0)
|
||||
print("set_orthographic 3")
|
||||
|
||||
#for _ in range(5):
|
||||
# vis.poll_events()
|
||||
|
||||
Reference in new issue
Block a user