U fb@sldZddlZddlZddlZddlmZddlZ ddl m Z ddl Z ddl mZddZGdd d eZdS) a0 Dataset model https://pytorch.org/docs/stable/torchvision/models.html#object-detection-instance-segmentation-and-person-keypoint-detection During training, the model expects both the input tensors, as well as a targets (list of dictionary), containing: boxes (FloatTensor[N, 4]): the ground-truth boxes in [x1, y1, x2, y2] format, with values between 0 and H and 0 and W labels (Int64Tensor[N]): the class label for each ground-truth box https://colab.research.google.com/github/benihime91/pytorch_retinanet/blob/master/demo.ipynb#scrollTo=0zNGhr6D7xGN N)Dataset) ToTensorV2)ImagecCsP|r.tjtjddtgtjddgdd}ntjtgtjddgdd}|S)z.Albumentations transformation of bounding boxsg?)p pascal_voc category_ids)format label_fields) bbox_params)AComposeHorizontalFlipr BboxParams)augment transformrh/home/ec2-user/SageMaker/vegetation-management-remars2022/remars2022-workshop/libs/deepforest/dataset.py get_transforms rc@s2eZdZdddiddfddZdd Zd d ZdS) TreeDatasetNTreerTFc Cst||_||_|dkr(t|d|_n||_|jj|_||_ ||_ t t g|_||_|jrtdi|_t|jD]B\}}tj|j|} tt| dd} | d|j|<q|dS)a Args: csv_file (string): Path to a single csv file with annotations. root_dir (string): Directory with all the images. transform (callable, optional): Optional transform to be applied on a sample. label_dict: a dictionary where keys are labels from the csv column and values are numeric labels "Tree" -> 0 Returns: If train: path, image, targets else: image N)rzPinning dataset to GPU memoryRGBfloat32)pdread_csv annotationsroot_dirrr image_pathunique image_names label_dicttrainr r rimage_converterpreload_imagesprint image_dict enumerateospathjoinnparrayropenconvertastype) selfcsv_filer transformsr r!r#idxximg_nameimagerrr__init__*s" zTreeDataset.__init__cCs t|jSN)lenrr/rrr__len__MszTreeDataset.__len__c sjrj|}n:tjjj|}tt | dd}| d}j rjjjj|k}i}|ddddgj t|d<|jfd d j tj|d <t|dd krtjd tjd}}t|d }t|dd }t|}||d}j|||fSj||d|d d}|d}t|d}t|}t|d}t|}||d}j|||fSj|d} | dSdS)Nrrrxminyminxmaxymaxboxescs j|Sr7)r )r3r9rrdz)TreeDataset.__getitem__..labelsr)r)dtype)r?rB)r5bboxesrr5rFr)r5)r#r%r'r(r)rrr*r+rr,r-r.r!rrvaluesfloatlabelapplyint64sumtorchzerosr from_numpyrollaxisrr") r/r2r5r4Zimage_annotationstargetsr?rB augmented convertedrr9r __getitem__PsJ          zTreeDataset.__getitem__)__name__ __module__ __qualname__r6r:rTrrrrr(s#r)__doc__r'pandasrnumpyr*torch.utils.dataralbumentationsr Zalbumentations.pytorchrrMPILrrrrrrrs