gpkg.object-detect.models 0.5.1
Object detection models (Guild AI)
License: Apache 2.0
Keywords: gpkg

gpkg.object-detect.models
#########################

*Object detection models (Guild AI)*

Models
######

faster-rcnn-resnet-101
======================

*Faster RCNN with ResNet 101*

Operations
^^^^^^^^^^

detect
------

*Detect images using a trained detector*

Flags
`````

**images**
  *Directory containing images to detect (required)*

evaluate
--------

*Evaluate a trained detector*

Flags
`````

**eval-examples**
  *Number of examples to evaluate (all available)*

export-and-freeze
-----------------

*Export a detection graph with checkpoint weights*

Flags
`````

**step**
  *Checkpoint step to use for the frozen graph (latest checkpoint)*

train
-----

*Train detector from scratch*

Flags
`````

**batch-size**
  *Number of examples in each training batch*

**clones**
  *Number of model clones. (1)

  This flag has no effect unless `legacy` is `yes`.

  Set this value to the number of available GPUs for multi-GPU training.

  *

**eval-examples**
  *Number of examples to evaluate after training (all available)

  This flag has no effect if `legacy` is `yes` (legacy train does not
  perform evaluation).

  *

**legacy**
  *Use legacy training for object detection (no)

  Multi GPU support is only available with legacy training.

  Unlike default training, legacy training does not perform an evaluation
  after training.

  Choices:
    yes  Use legacy training (select for multi GPU support)
    no   Use default training (does not support multiple GPUs)

  *

**quantize**
  *Whether or not to quantize model weights (no)*

**quantize-delay**
  *Number of steps to train before quantizing*

**train-steps**
  *Number of steps to train (train indefinitely)*

transfer-learn
--------------

*Train detector using transfer learning*

Flags
`````

**batch-size**
  *Number of examples in each training batch*

**clones**
  *Number of model clones. (1)

  This flag has no effect unless `legacy` is `yes`.

  Set this value to the number of available GPUs for multi-GPU training.

  *

**eval-examples**
  *Number of examples to evaluate after training (all available)

  This flag has no effect if `legacy` is `yes` (legacy train does not
  perform evaluation).

  *

**legacy**
  *Use legacy training for object detection (no)

  Multi GPU support is only available with legacy training.

  Unlike default training, legacy training does not perform an evaluation
  after training.

  Choices:
    yes  Use legacy training (select for multi GPU support)
    no   Use default training (does not support multiple GPUs)

  *

**quantize**
  *Whether or not to quantize model weights (no)*

**quantize-delay**
  *Number of steps to train before quantizing*

**train-steps**
  *Number of steps to train (train indefinitely)*


faster-rcnn-resnet-50
=====================

*Faster RCNN with ResNet 50*

Operations
^^^^^^^^^^

detect
------

*Detect images using a trained detector*

Flags
`````

**images**
  *Directory containing images to detect (required)*

evaluate
--------

*Evaluate a trained detector*

Flags
`````

**eval-examples**
  *Number of examples to evaluate (all available)*

export-and-freeze
-----------------

*Export a detection graph with checkpoint weights*

Flags
`````

**step**
  *Checkpoint step to use for the frozen graph (latest checkpoint)*

train
-----

*Train detector from scratch*

Flags
`````

**batch-size**
  *Number of examples in each training batch*

**clones**
  *Number of model clones. (1)

  This flag has no effect unless `legacy` is `yes`.

  Set this value to the number of available GPUs for multi-GPU training.

  *

**eval-examples**
  *Number of examples to evaluate after training (all available)

  This flag has no effect if `legacy` is `yes` (legacy train does not
  perform evaluation).

  *

**legacy**
  *Use legacy training for object detection (no)

  Multi GPU support is only available with legacy training.

  Unlike default training, legacy training does not perform an evaluation
  after training.

  Choices:
    yes  Use legacy training (select for multi GPU support)
    no   Use default training (does not support multiple GPUs)

  *

**quantize**
  *Whether or not to quantize model weights (no)*

**quantize-delay**
  *Number of steps to train before quantizing*

**train-steps**
  *Number of steps to train (train indefinitely)*

transfer-learn
--------------

*Train detector using transfer learning*

Flags
`````

**batch-size**
  *Number of examples in each training batch*

**clones**
  *Number of model clones. (1)

  This flag has no effect unless `legacy` is `yes`.

  Set this value to the number of available GPUs for multi-GPU training.

  *

**eval-examples**
  *Number of examples to evaluate after training (all available)

  This flag has no effect if `legacy` is `yes` (legacy train does not
  perform evaluation).

  *

**legacy**
  *Use legacy training for object detection (no)

  Multi GPU support is only available with legacy training.

  Unlike default training, legacy training does not perform an evaluation
  after training.

  Choices:
    yes  Use legacy training (select for multi GPU support)
    no   Use default training (does not support multiple GPUs)

  *

**quantize**
  *Whether or not to quantize model weights (no)*

**quantize-delay**
  *Number of steps to train before quantizing*

**train-steps**
  *Number of steps to train (train indefinitely)*


pet-images
==========

*Annotated images from Oxford-IIIT pet dataset*

Operations
^^^^^^^^^^

prepare
-------

*Prepares pet images for training*


ssd-mobilenet-v2
================

*SSD with MobileNet v2*

Operations
^^^^^^^^^^

detect
------

*Detect images using a trained detector*

Flags
`````

**images**
  *Directory containing images to detect (required)*

evaluate
--------

*Evaluate a trained detector*

Flags
`````

**eval-examples**
  *Number of examples to evaluate (all available)*

export-and-freeze
-----------------

*Export a detection graph with checkpoint weights*

Flags
`````

**step**
  *Checkpoint step to use for the frozen graph (latest checkpoint)*

**tflite**
  *Whether or not to export graph with support for TensorFlow Lite (no)

  Choices:
    yes  Export graph with support for TensorFlow Lite
    no   Export graph normally

  *

train
-----

*Train detector from scratch*

Flags
`````

**batch-size**
  *Number of examples in each training batch*

**clones**
  *Number of model clones. (1)

  This flag has no effect unless `legacy` is `yes`.

  Set this value to the number of available GPUs for multi-GPU training.

  *

**eval-examples**
  *Number of examples to evaluate after training (all available)

  This flag has no effect if `legacy` is `yes` (legacy train does not
  perform evaluation).

  *

**legacy**
  *Use legacy training for object detection (no)

  Multi GPU support is only available with legacy training.

  Unlike default training, legacy training does not perform an evaluation
  after training.

  Choices:
    yes  Use legacy training (select for multi GPU support)
    no   Use default training (does not support multiple GPUs)

  *

**quantize**
  *Whether or not to quantize model weights (no)*

**quantize-delay**
  *Number of steps to train before quantizing*

**train-steps**
  *Number of steps to train (train indefinitely)*

transfer-learn
--------------

*Train detector using transfer learning*

Flags
`````

**batch-size**
  *Number of examples in each training batch*

**clones**
  *Number of model clones. (1)

  This flag has no effect unless `legacy` is `yes`.

  Set this value to the number of available GPUs for multi-GPU training.

  *

**eval-examples**
  *Number of examples to evaluate after training (all available)

  This flag has no effect if `legacy` is `yes` (legacy train does not
  perform evaluation).

  *

**legacy**
  *Use legacy training for object detection (no)

  Multi GPU support is only available with legacy training.

  Unlike default training, legacy training does not perform an evaluation
  after training.

  Choices:
    yes  Use legacy training (select for multi GPU support)
    no   Use default training (does not support multiple GPUs)

  *

**quantize**
  *Whether or not to quantize model weights (no)*

**quantize-delay**
  *Number of steps to train before quantizing*

**train-steps**
  *Number of steps to train (train indefinitely)*


voc-2008-images
===============

*Visual Object Classes Challenge 2008 images*

Operations
^^^^^^^^^^

prepare
-------

*Prepare images annotated using Pascal VOC format*

Flags
`````

**random-seed**
  *Seed used for train/validation split (randomly generated)*

**val-split**
  *Percentage of images reserved for validation (30)*


voc-annotated-images
====================

*Images annotated using Pascal VOC format*

Operations
^^^^^^^^^^

prepare
-------

*Prepare images annotated using Pascal VOC format*

Flags
`````

**annotations**
  *Directory containing image annotations (required)*

**images**
  *Directory containing images to prepare (required)*

**random-seed**
  *Seed used for train/validation split (randomly generated)*

**val-split**
  *Percentage of images reserved for validation (30)*