o 1ÎjJKã@spddlZddlmZddlmZddlmZddlmZddl m Z dd l m Z dd l mZGd d „d e ƒZdS) éNé)ÚDEFAULT_CACHE_DIR)Ú parse_device)Údownload)Úabspathé)Ú BaseModel)Ú CLIArgument)ÚCompletedProcessc@s4eZdZdZ           d$deded ed ed ed ed edededededefdd„Z     d%deded ed edededefdd„Z  d&deded ededef dd„Z d'dd„Z dededefdd„Z  d&deded ededef d d!„Z      d(dededed ed edededefd"d#„ZdS))ÚSegModelzSemantic Segmentation ModelNÚgpuFÚOFFTÚ batch_sizeÚ learning_rateÚ epochs_itersÚipsÚdeviceÚ resume_pathÚdy2stÚampÚ num_workersÚuse_vdlÚsave_dirÚreturnc ! KsÐ|j ¡} g}|dur| td|ƒ¡|dur| td|ƒ¡|dur+| td|ƒ¡|dur=t|ƒ\}}| td|ƒ¡|  dd¡}|durR|durRtj |d¡}|dur˜t |ƒ}tj  |¡dkrit |›dƒ‚tj  |¡svt |›d ƒ‚tj |¡}tj |d ¡}tj  |¡st |›d ƒ‚| td |ƒ¡|rŸ|  |¡| r¨| td ƒ¡| dur±t | ƒ} n t tj dd¡ƒ} | td| ƒ¡|  dd¡}|durÔ| td|ƒ¡|  dd¡}|  dd¡}|  dd¡}|  dd¡}|durø| td|ƒ¡|  dd¡}|dur | td|ƒ¡|  dd¡}|dur!| tdg|¢RŽ¡|  dd¡}|durØ| dd¡}| dd¡}| dd¡}| dd¡}| d d¡} |  |¡| d!d¡}|  | d"d¡¡|  | d#d¡¡|dur~t|tƒsvJd$ƒ‚| td%|ƒ¡| dur•t| tƒsJd&ƒ‚| td'| ƒ¡|dur¬t|tƒs¤Jd(ƒ‚| td)|ƒ¡|d*vrÁ| td+d,ƒ¡| td-|ƒ¡|dur×| ¡D] \}}t|ƒtj|<qÊnA|durò|d.krò| td+d,ƒ¡| td-|ƒ¡| durÿ| td'| ƒ¡|dur | td%|ƒ¡|dur| td)|ƒ¡|  d/d¡}|  d0d¡}|  d/|¡|  d1|j¡|r;|  d0|¡| | ¡| ¡} |  | ¡|jj| |||| |d2WdƒS1sawYdS)3ahtrain self Args: batch_size (int, optional): the train batch size value. Defaults to None. learning_rate (float, optional): the train learning rate value. Defaults to None. epochs_iters (int, optional): the train epochs value. Defaults to None. ips (str, optional): the ip addresses of nodes when using distribution. Defaults to None. device (str, optional): the running device. Defaults to 'gpu'. resume_path (str, optional): the checkpoint file path to resume training. Train from scratch if it is set to None. Defaults to None. dy2st (bool, optional): Enable dynamic to static. Defaults to False. amp (str, optional): the amp settings. Defaults to 'OFF'. num_workers (int, optional): the workers number. Defaults to None. use_vdl (bool, optional): enable VisualDL. Defaults to True. save_dir (str, optional): the directory path to save train output. Defaults to None. Returns: CompletedProcess: the result of training subprocess execution. 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Returns: CompletedProcess: the result of predicting subprocess execution. rWú --image_pathNrr Úpredictr")r5r6rr7r rr9r:r;rIrJrKrLr]) rMrVr[rrrNr5rOrPrQrSrTrTrUr]ós$      $þzSegModel.predictc KsÔ|j ¡}g}t|ƒ}| td|ƒ¡|dur%t|ƒ\}} | td|ƒ¡|dur.t|ƒ}n ttj dd¡ƒ}| td|ƒ¡|  |¡|  ¡} |  | ¡|j   | |||¡} | WdƒS1scwYdS)ÚanalyserWNrr Zanalysisr")r5r6rr7r rr9r:r;rIrJrKrLr^) rMrVrrrrNr5rOrPrQrSrZrTrTrUr^ s"      $ýzSegModel.analysec Ksš|j ¡}g}| d¡st|ƒ}ntj |¡}tj t|¡}t ||ddd|}|  t d|ƒ¡|dur9t|ƒ}n ttj dd¡ƒ}|  t d|ƒ¡|  d d¡}|dur_|  t d g|¢RŽ¡z|d } Wn |  d d¡} Y| dur„| d vs|Jd ƒ‚|  t d| ƒ¡|  dd¡} |  dd¡} |  d| ¡|  d|j¡| r¥|  d| ¡| |¡| ¡} | | ¡|j | |d¡WdƒS1sÆwYdS)a3export the dynamic model to static model Args: weight_path (str): the model weight file path that used to export. save_dir (str): the directory path to save export output. Returns: CompletedProcess: the result of exporting subprocess execution. ÚhttpT)Zprint_progressÚ overwriterWNr Úexportr"r)r*Ú output_op)ZsoftmaxZargmaxÚnonez2`output_op` must be 'none', 'softmax' or 'argmax'.z --output_opr2r3Fr4)r5r6Ú startswithrr9r:r<r;rrr7r r8rGrHrIrJrKrLra) rMrVrrNr5rOÚfilenameZ save_pathr)rbr2r3rSrTrTrUra:sH        ü       $þzSegModel.exportÚ model_dirc Ksä|j ¡}g}t|ƒ}t|ƒ}| td|ƒ¡|dur)t|ƒ\}} | td|ƒ¡|dur2t|ƒ}n ttj dd¡ƒ}| td|ƒ¡|  |¡|  ¡} |  | ¡tj |d¡} |j   | ||¡WdƒS1skwYdS)aêpredict image using infernece model Args: model_dir (str): the directory path of inference model files that would use to predict. input_path (str): the path of image that would be predict. device (str, optional): the running device. Defaults to 'gpu'. save_dir (str, optional): the directory path to save output. Defaults to None. Returns: CompletedProcess: the result of inferring subprocess execution. r\Nrr Úinferr"z inference.yml)r5r6rr7r rr9r:r;rIrJrKrLrg) rMrfr[rrrNr5rOrPrQrSZdeploy_config_pathrTrTrUrgvs$      $ýzSegModel.infercKst|j ¡} g} g} t|ƒ}|  td|ƒ¡|dur!|  td|ƒ¡|dur-|  td|ƒ¡|dur9|  td|ƒ¡|durKt|ƒ\} } |  td| ƒ¡|rT|  tdƒ¡|dur]t|ƒ}n ttj dd ¡ƒ}|  td |ƒ¡|  td tj |d ¡ƒ¡|  d d¡}|dur|  td g|¢RŽ¡|  |¡|  ¡}|   |¡|j  || | ||¡WdƒS1s³wYdS)acompression model Args: weight_path (str): the path to weight file of model. batch_size (int, optional): the batch size value of compression training. Defaults to None. learning_rate (float, optional): the learning rate value of compression training. Defaults to None. epochs_iters (int, optional): the epochs or iters of compression training. Defaults to None. device (str, optional): the device to run compression training. Defaults to 'gpu'. use_vdl (bool, optional): whether or not to use VisualDL. Defaults to True. save_dir (str, optional): the directory to save output. 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