How to use parallel_simple method in autotest

Best Python code snippet using autotest_python Github


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1import os2import numpy as np3import torch4import argparse5from simulateTest.AutoGraspShapeCoreUtil import AutoGraspUtil6# parser = argparse.ArgumentParser(description='ShapeNetSem Grasp testing')7# parser.add_argument('-t', '--testFile', default='prediction/500ntop10.txt', type=str, metavar='FILE', help='testFile path')8# # parser.add_argument('-n', '--samplePerObject', default=10, type=int, metavar='N', help='sample num per object')9# parser.add_argument('-p', '--processNum', default=18, type=int, metavar='N', help='process num using')10# parser.add_argument('-w', '--haveWidth', default=1, type=int, metavar='N', help='0 : no width ; 1 : have width')11# parser.add_argument('--gripperFile', default='/data/shapeNet/annotator2/parallel_simple.urdf', type=str, metavar='FILE', help='gripper file')12# parser.add_argument('--objMeshRoot', default='/data/shapeNet/urdf', type=str, metavar='PATH', help='obj mesh path')13parser = argparse.ArgumentParser(description='ShapeNetSem Grasp testing')14parser.add_argument('-t', '--testFile', default='gpnet_data/prediction/nms_poses_view0.txt', type=str, metavar='FILE', help='testFile path')15# parser.add_argument('-n', '--samplePerObject', default=10, type=int, metavar='N', help='sample num per object')16parser.add_argument('-p', '--processNum', default=10, type=int, metavar='N', help='process num using')17# parser.add_argument('-w', '--haveWidth', default=0, type=int, metavar='N', help='0 : no width ; 1 : have width')18parser.add_argument('-w', "--width", action="store_true", dest="width", default=False, help="turn on this param if test file contains width.")19parser.add_argument('--gripperFile', default='gpnet_data/gripper/parallel_simple.urdf', type=str, metavar='FILE', help='gripper file')20parser.add_argument('--objMeshRoot', default='gpnet_data/urdf', type=str, metavar='PATH', help='obj mesh path')21def getObjStatusAndAnnotation(testFile, haveWidth=False):22 with open(testFile, 'r') as testData:23 lines = testData.readlines()24 objIdList = []25 quaternionDict = {}26 centerDict = {}27 # 0: scaling 1~3: position 4~7: orientation 8: staticFrictionCoeff28 objId = 'invalid'29 objCounter = -130 annotationCounter = -131 for line in lines:32 # new object33 msg = line.strip()34 if len(msg.split(',')) < 2 :35 objId = msg.strip()36 # skip invalid37 # begin38 objCounter += 139 objIdList.append(objId)40 quaternionDict[objId] = np.empty(shape=(0, 4), dtype=np.float)41 centerDict[objId] = np.empty(shape=(0, 3), dtype=np.float)42 annotationCounter = -143 # read annotation44 else:45 # skip invalid object46 if objId == 'invalid':47 continue48 # begin49 annotationCounter += 150 pose = msg.split(',')51 # print(objId, annotationCounter)52 if haveWidth:53 length = float(pose[0]) * 0.085 # arbitrary value, will not be used in AutoGrasp54 length = length if length < 0.085 else 0.08555 position = np.array([float(pose[1]), float(pose[2]), float(pose[3])])56 quaternion = np.array([float(pose[4]), float(pose[5]), float(pose[6]), float(pose[7])])57 # quaternion = quaternion[[1, 2, 3, 0]]58 else:59 length = 0.000 # arbitrary value, will not be used in AutoGrasp60 position = np.array([float(pose[0]), float(pose[1]), float(pose[2])])61 quaternion = np.array([float(pose[3]), float(pose[4]), float(pose[5]), float(pose[6])])62 # quaternion = quaternion[[1, 2, 3, 0]]63 # print(objCounter, annotationCounter)64 quaternionDict[objId] = np.concatenate((quaternionDict[objId], quaternion[None, :]), axis=0)65 centerDict[objId] = np.concatenate((centerDict[objId], position[None, :]), axis=0)66 return quaternionDict, centerDict, objIdList67if __name__ == "__main__":68 cfg = parser.parse_args()69 objMeshRoot = cfg.objMeshRoot70 processNum = cfg.processNum71 gripperFile = cfg.gripperFile72 haveWidth = cfg.width73 testInfoFile = cfg.testFile74 logFile = cfg.testFile[:-4] + '_log.csv'75 open(logFile, 'w').close()76 simulator = AutoGraspUtil()77 quaternionDict, centerDict, objIdList = getObjStatusAndAnnotation(testInfoFile, haveWidth)78 for objId in objIdList:79 q = quaternionDict[objId]80 c = centerDict[objId]81 simulator.addObject2(82 objId=objId,83 quaternion=q,84 translation=c85 )86 simulator.parallelSimulation(87 logFile=logFile,88 objMeshRoot=objMeshRoot,89 processNum=processNum,90 gripperFile=gripperFile,91 )92 annotationSuccessDict = simulator.getSuccessData(logFile=logFile)93 # print(top 10% 30% 50% 100%)94 top10, top30, top50, top100 = simulator.getStatistic(annotationSuccessDict)...

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...31toolbox.register("mutate", mutGaussianInt, mu=mu, sigma=sigma, indpb=0.25)32toolbox.register("select", tools.selBest)33if __name__ == "__main__":34 start_time = time.time()35 pop, log, hof, history = parallel_simple(toolbox, pop_sz, cxpb, mutpb, ngen, n_jobs=4)36 print("total runtime:", time.time() - start_time)37 print("Best individual is: %s\nwith fitness: %s" % (hof[0], hof[0].fitness.values[0]))38 print("Final population:\n", pop)39 print("Log:\n", log)40 output = []41 for i in hof:42 output.append(i + [[0]])43 print(i + [[0]])44 output = np.array(output)45 np.savetxt('ga_results_backup2.csv', output, fmt='%10.5f', delimiter=',')46 gene_order = []47 for i in history.genealogy_history:48 gene_order.append(history.genealogy_history[i])49 gene_order = np.array(gene_order)...

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