Package organization

[bw4sz]

Before we get going on travis, let's do a few things.

• For the package to be installed all dependencies need to be in setup.py

NeonTreeEvaluation_python/setup.py

Line 13 in 7f4669e

requirements = [ ]

• pip install . should install locally in a clean conda env

• local pytests pass that cover the main functions

• all data in a single location

• source code and runtime code in separate locations (splitting

  NeonTreeEvaluation_python/evaluation.py

  Line 104 in 7f4669e

  sub = gp.read_file('./submission.csv')

  )

• doc strings for the outward facing functions. I tend to use google docstring

for example

    def evaluate_generator(self,
                           annotations,
                           comet_experiment=None,
                           iou_threshold=0.5,
                           max_detections=200):
        """Evaluate prediction model using a csv fit_generator.

        Args:
            annotations (str): Path to csv label file, labels are in the
                format -> path/to/image.png,x1,y1,x2,y2,class_name
            comet_experiment(object): A comet experiment class objects to track
            iou_threshold(float): IoU Threshold to count for a positive detection
                (defaults to 0.5)
            max_detections (int): Maximum number of bounding box predictions

        Return:
            mAP: Mean average precision of the evaluated data

that way we can just generate readthedocs from sphinx easily.