bias: Whether conv layers have bias or not. adaptive: Whether to use adaptive threshold training or not. smooth: If true, use

default_evaluation_params: Default parameters to use for the validation and evaluation.

Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a ResNet-50 model with deformable conv. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Method evaluate_method: evaluate method and returns the results Results. Dictionary with the following values: - method (required

pred: one or two heatmaps of shape (N, 1, H, W), the losses of tow heatmaps are added together. gt: (N, 1, H, W)

Args: pred: (N, 1, H, W). gt: (N, H, W). mask: (N, H, W).

Args: pred: shape :math:`(N, 1, H, W)`, the prediction of network gt: shape :math:`(N, 1, H, W)`, the target

Returns all points, confindences and transcriptions of a file in lists. Valid line formats: xmin,ymin,xmax,ymax,[confidence],[transcription]

Returns an array with the contents (filtered by fileNameRegExp) of a ZIP file. The key's are the names or the file or the capturing group def

Returns an array with the contents (filtered by fileNameRegExp) of a ZIP file. The key's are the names or the file or the capturing group def

Returns an array with the entries of the ZIP file that match with the regular expression. The key's are the names or the file or the capturin

This process validates a method, evaluates it and if it succed generates a ZIP file with a JSON entry for each sample. Params: p: Diction

This process validates a method Params: default_evaluation_params_fn: points to a function that returns a dictionary with the default par

requied keys: image, polygons, ignore_tags, filename adding keys: mask

Constructs a ResNet-101 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a ResNet-152 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a ResNet-34 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Method validate_data: validates that all files in the results folder are correct (have the correct name contents). Va

This function validates that all lines of the file calling the Line validation function for each line