Person Reidentifier

Implementation with Command Line Interface of the work done for my degree final project "Appereance and context information combination for re-identificaton in sports competitions" ("Combinación de apariencia e información de contexto para la re-identificación en competiciones deportivas").

With this implementation you can:

• Run the studied body detectors and get the body images or bounding boxes of the bodies in a given image.
• Generate a representative embedding from a body image using studied body embedding generators.
• Compute the CMC curve of a given gallery set and query set, using one of the proposed heuristics.
• Test the whole system from a video feed, using a specified gallery set.

Requirements

• Python >= 3.7.
• Pip >= 20.

Project set up

In your system or virtual Python environment, install the requirements/dependencies:

pip install -r requirements.txt

Then you can use it by executing the personIdentifier.py script:

./personReidentifier.py

CLI interface manual

Program configuration

Option	Description
-h, --help	Shows the help message and exit.
--silent	Runs program in silent mode (no verbose).

Embedding generation configuration

Option	Description
--alignedreid	Uses AlignedReId++ for body embedding generation.
--abd	Uses Attentive but Diverse Network for body embedding generation.
--embeddingGeneratorWeights weights_file	Embedding generator weights file.
--embeddingGeneratorClasses classes_number	Embedding generator number of classes.

Detection configuration

Option	Description
--mtcnn	Uses MTCNN for face detection.
--yolo	Uses YOLOv3 for person detection.
--faster	Uses FasterRCNN for person detection.
--mask	Uses `MaskRCNN for person detection.
--bodyDetectorWeights weights_path	Body detector weights file.
--bodyDetectorConfig configuration_file_path	Body detector configuration file. Only needed for YOLOv3.
--detectionThreshold threshold_float	Specifies the detection threshold. Default value: 0.8

Features

Embedding generation

Option	Description
--embedding image_file	Returns embedding of the given body. Default embedding generator: AlignedReId++.
--savePath save_embedding_path	Embedding save path (use .h5 extension).

Body detection

Option	Description
--detection image_path	Returns bodies of the given image in the specified folder using --saveFolder option. Default body detector: MaskRCNN.
--boundingBox	Draws bounding boxes in image instead of getting the body image.
--saveFolder folder_path	Specifies the save folder for the --detection option.

System evaluation: CMC curves, heuristics

CMC curve

Dataset must follow the next structure:

  Root
  |
  |
  |     Identity
  |--   0
  |     |
  |     |   
  |     |     Location
  |     |--   0
  |     |     |
  |     |     |
  |     |     |     Image number
  |     |     |--   0
  |     |     |
  |     |     |--   1
  |     |     |
  |     |     |--   2
  |     |     |
  |     |     |--   ...
  |     |
  |     |
  |     |
  |     |--   1
  |     |
  |     |--   2
  |     |
  |     |--   ...
  |
  |
  |
  |--   1
  |
  |--   2
  |
  |--   3
  |
  |--   ...

Option	Description
--cmc	Returns the CMC curve discrete values of the given query and gallery.
--plot	Plots the calculated CMC curve.
--ids ids_file_path	The ids list files.
--query query_directory_path	The query embeddings directory.
--gallery gallery_directory_path	The gallery embeddings directory.
--queryLocation location_number	The choosen query location in the dataset.
--galleryLocation location_number	The choosen gallery location in the dataset.
--oneIndexed	Check this option if the dataset indexes starts at 1.
--topNum top_number	Top number of CMC curve.

Heuristic configuration

Time heuristic

Option	Description
--timeHeuristic	Display the CMC curve using time heuristic of the given query and gallery.
--raceRanking rank_file_path	Previous race ranking file for CMC curve for heuristics.
--windowSize integer	Window size for time heuristic. Default value: 30.
--shiftSize integer	Shift size for time heuristic. Default value: 1.
--shiftProp float	Shift proportion for time heuristic. Default value: 1.

Space heuristic

Option	Description
--spaceHeuristic	Display the CMC curve using space heuristic of the given query and gallery.
--fps integer	FPS for space heuristic. Default value: 5.
--timeout float	Timeout for space heuristic. Default value: 10.

Complete system test

Option	Description
--video video_path	Runs system with specified video file.
--camera	Runs system using system camera.

Open set based problem parameters (experimental)

This features has not been tested and were implemented for experimental intentions only. Further work in this area can be made, as told in the project report.

Option	Description
--openWorldThreshold float	The minimum value to consider an identity as equal as one in the gallery.
--maxDescriptors integer	The maximum number of descriptors per gallery.

Credits:

Models and pretrained weights

• MaskRCNN implementation and pre-trained weights.
• FasterRCNN frozen graph and weights.
• YOLOv3 weights and configuration file.
• AlignedReId++ implementation and pre-trained weights.
• ABD-Net implementation and pre-trained weights.

Libraries

• Tensorflow
• PyTorch
• Scikit-Learn
• Pillow
• Keras
• OpenCV
• Matplotlib
• Numpy
• MTCNN

Tools

• Git
• PyCharm
• Visual Studio Code