Object detection models (Guild AI)
Project description
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)*
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
File details
Details for the file gpkg.object_detect.models-0.5.1-py2.py3-none-any.whl
.
File metadata
- Download URL: gpkg.object_detect.models-0.5.1-py2.py3-none-any.whl
- Upload date:
- Size: 6.2 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.9.1 pkginfo/1.4.2 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.19.6 CPython/2.7.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b08d3afdf3d51c6e7e50ad324e557975d3a211eef4192e42daab478c214a9e3c |
|
MD5 | aee7cfce7d73412350ef4d650e01d5f7 |
|
BLAKE2b-256 | 2ff494f1f0b43c12f9f7a6c3015568bcd5f087fccedbf6b0c336c88948410f83 |