Python cntk.layers() Examples

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Example #1
Source File: FasterRCNN.py    From cntk-hotel-pictures-classificator with MIT License 6 votes vote down vote up 
def create_faster_rcnn_predictor(base_model_file_name, features, scaled_gt_boxes, dims_input):
    # Load the pre-trained classification net and clone layers
    base_model = load_model(base_model_file_name)
    conv_layers = clone_conv_layers(base_model)
    fc_layers = clone_model(base_model, [pool_node_name], [last_hidden_node_name], clone_method=CloneMethod.clone)

    # Normalization and conv layers
    feat_norm = features - normalization_const
    conv_out = conv_layers(feat_norm)

    # RPN and prediction targets
    rpn_rois, rpn_losses = \
        create_rpn(conv_out, scaled_gt_boxes, dims_input, proposal_layer_param_string=cfg["CNTK"].PROPOSAL_LAYER_PARAMS)
    rois, label_targets, bbox_targets, bbox_inside_weights = \
        create_proposal_target_layer(rpn_rois, scaled_gt_boxes, num_classes=globalvars['num_classes'])

    # Fast RCNN and losses
    cls_score, bbox_pred = create_fast_rcnn_predictor(conv_out, rois, fc_layers)
    detection_losses = create_detection_losses(cls_score, label_targets, rois, bbox_pred, bbox_targets, bbox_inside_weights)
    loss = rpn_losses + detection_losses
    pred_error = classification_error(cls_score, label_targets, axis=1)

    return loss, pred_error