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)*
#########################
*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)*
1 maintainer
Metadata
1 maintainer
Release files for gpkg.object-detect.models 0.5.1
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