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Mjolnir65/FasterRCNN

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rootdetection__pycache__generalized_rcnn.cpython-37.pyc
generalized_rcnn.cpython-37.pyc51 linesDownload Raw Back to __pycache__
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mZGdd�dej�ZdS)	z,6Implements the Generalized R-CNN framework7�N)�OrderedDict)�Dict�List�Optional�Tuple�Union)�nn�Tensor)�_log_api_usage_oncecsPeZdZdZejejejejdd��fdd�Zejj	dd��Z8d9dd	�Z�ZS)�GeneralizedRCNNad10    Main class for Generalized R-CNN.11 12    Args:13        backbone (nn.Module):14        rpn (nn.Module):15        roi_heads (nn.Module): takes the features + the proposals from the RPN and computes16            detections / masks from it.17        transform (nn.Module): performs the data transformation from the inputs to feed into18            the model19    N)�backbone�rpn�	roi_heads�	transform�returncs4t���t|�||_||_||_||_d|_dS)NF)�super�__init__r20rrr
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|j|�\}}|j	�||j|�}i}|�|�|�|�tj���r2|j�s*t�d�d|_||fS|�||�SdS)a28        Args:29            images (list[Tensor]): images to be processed30            targets (list[Dict[str, Tensor]]): ground-truth boxes present in the image (optional)31 32        Returns:33            result (list[BoxList] or dict[Tensor]): the output from the model.34                During training, it returns a dict[Tensor] which contains the losses.35                During testing, it returns list[BoxList] contains additional fields36                like `scores`, `labels` and `mask` (for Mask R-CNN models).37 38        NFz0targets should not be none when in training mode�boxes�������z:Expected target boxes to be a tensor of shape [N, 4], got �.z0Expected target boxes to be of type Tensor, got �����zJexpecting the last two dimensions of the Tensor to be H and W instead got r�)�dimzLAll bounding boxes should have positive height and width. Found invalid box z for target at index �0z=RCNN always returns a (Losses, Detections) tuple in scriptingT)r�torch�_assert�39isinstancer	�len�shape�type�appendr�	enumerate�any�where�tolistr�tensorsrr
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