Completed documentation
Signed-off-by: Jim Martens <github@2martens.de>
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@ -20,10 +20,14 @@ Provides CLI actions.
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Functions:
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config(...): handles the config component
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train(...): trains a network
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test(...): evaluates a network
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val(...): runs predictions on the validation data
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prepare(...): prepares the SceneNet ground truth data
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train(...): trains a network
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test(...): tests a network
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evaluate(...): evaluates prediction results
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visualise(...): visualises ground truth
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visualise_metrics(...): visualises evaluation results
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visualise_all(...): creates figure for specific variants and thresholds
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measure_mapping(...): measures the number of instances per COCO class
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"""
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import argparse
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from typing import Any
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@ -20,8 +20,11 @@ Functionality to load data into Tensorflow data sets.
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Functions:
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load_coco_train(...): loads the COCO training data into a Tensorflow data set
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load_coco_val(...): loads the COCO validation data into a Tensorflow data set
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load_coco_val_ssd(...): loads the COCO validation data using the ssd_keras data pipeline
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load_scenenet_data(...): loads the SceneNet RGB-D data into a Tensorflow data set
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prepare_scenenet_data(...): prepares the SceneNet RGB-D data and returns it in Python format
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group_bboxes_to_images(...): groups bounding boxes to images
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clean_dataset(...): cleans a COCO data set and returns cleaned version
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"""
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from typing import Callable
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from typing import Generator
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@ -248,6 +251,16 @@ def _load_images_callback(resized_shape: Sequence[int]) -> Callable[
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def group_bboxes_to_images(file_names: Sequence[str], bboxes: Sequence[Sequence[int]]) -> Tuple[List[str],
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List[List[List[int]]]]:
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"""
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Groups bounding boxes to images.
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Args:
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file_names: list of image file names
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bboxes: list of bounding boxes
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Returns:
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tuple of file names and corresponding lists of bounding boxes
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"""
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return_labels = {}
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for file_name, bbox in zip(file_names, bboxes):
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if file_name not in return_labels:
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