create_dl_train_param (DLModelHandle, MaxNumEpochs, [], EnableDisplay,73,'anomaly', TrainParamAnomaly, TrainParam)*---开始训练 train_dl_model (DLDataset, DLModelHandle, TrainParam,0, TrainResults, TrainInfos, EvaluationInfos) dev_disp_text ('Press Run (F5) to continue','window','bottom',...
preprocess_dl_samples (DLSampleInference, DLPreprocessParam) apply_dl_model (DLModelHandle, DLSampleInference, [], DLResult) *为一个示例可视化不同的图像、注释和推理结果。 dev_display_dl_data (DLSampleInference, DLResult, DLDataset, 'bbox_result', [], WindowDict) dev_disp_text ('Press Run...
read_dl_samples (DLDataset, ShuffledIndices[0:9], DLSampleBatchDisplay) create_dict (WindowHandleDict) for Index := 0 to |DLSampleBatchDisplay| - 1 by 1 dev_display_dl_data (DLSampleBatchDisplay[Index], [], DLDataset, ['image','segmentation_image_ground_truth'], [], WindowHandleDict...
处理的步骤包括给每一个DLSamples样本创建数据字典,获取样本的图像,从图像中获取标注框区域,存入DLSamples数据字典中等。 预览预处理数据集 在开始训练之前,建议检查一遍预处理的数据集。使用get_dict_tuple算子从数据字典DLDataset中提取样本DatasetSamples。接着对其进行排序。读取排序后的样本并使用dev_display_dl_data...
evaluate_dl_model preprocess_dl_samples preprocess_dl_model_images preprocess_dl_model_augmentation_data train_dl_model The following new procedures are now available: convert_ocr_detection_result_to_object_detection dev_display_dl_invalid_samples ...
dev_display_dl_dataThe following new procedures are now available: preprocess_dl_model_3d_data gen_dl_samples_3d_gripping_point_detection gen_dl_3d_gripping_points_and_poses estimate_dl_3d_sorting_directionA new reference manual chapter "3D-Matching/3D-Gripping-Point-Detection" has been added....
可用函数dev_display_dl_data对预处理后的数据进行可视化。 模型训练 本部分介绍了DL对象检测模型的训练。在HDevelop示例detect_pills_deep_learning_2_train.hdev中也显示了单个步骤。 1.设置训练参数并将它们存储在字典TrainingParam中。这些参数包括: 2.超参数,请参阅下面的“模型参数和超参数”一节以及深度学习一...
求助深度学习dev_display_dl_data算子该怎么移植到C# hehe1 1⁄602 2024-6-30 08:54 给大家推荐一款深度学习训练软件 易明AI视觉检测 9⁄1577 2024-6-26 18:10 可为测控METIS 深度学习软件介绍资料 amos_yang 0⁄543 2024-6-14 15:19 开源深度学习框架训练、Hlacon运行模型? Atom_Du 0⁄...
dev_display_dl_data (DLSampleBatchDisplay[Index], [], DLDataset, ['image','segmentation_image_...
set_calib_data_calib_object (CalibDataID, 0, CaltabName)//定义一个标定对象// * Start the loop over the calibration images for i := 0 to 10 by 1 * Read and display the calibration images read_image (ImageL, ImgPath+'calib_distorted_l_'+i$'03d') ...