Model Checkpoint Packages
Model Checkpoint packages provide saved model checkpoints and associated Model Entities, along with full instructions on usage, for a variety of popular models for different tasks. The Model Checkpoint packages act as guides for how to prepare your own custom models in GenSynth for your development needs, and can even be used as the basis for your custom models with specific limitations on the format of the dataset. Available Model Checkpoint packages include:
Package Name | Description | Applies to: |
avod_kitti_3d | Provides an untrained Aggregate View Object Detection (AVOD) checkpoint suitable to work with the KITTI Car 3D Object Detection (kitti_car_3d) dataset. | 1.12+ |
centernet_resnet50_32x512x512 | Provides an example checkpoint of the centernet-ResNet50 model. | 1.13+ |
depthnet_kitti | Provides a DepthNet checkpoint with pre-trained weights. This model is compatible with KITTI Depth data. | 1.12+ |
dncnn_128 | A model checkpoint pacjage demonstrating the Denoising Convolutionsal Neural Network (DCNN). | 1.14+ |
frcnn_resnet50_16x416x416 | Provides a Faster-R-CNN (ResNet50) model, pre-trained on the VOC dataset. It requires input batch size 16 and input image 416x416x3. | 1.12+ |
edge_speechnet_residual15 | Provides an untrained checkpoint for Edge SpeechNet model. | 1.11+ |
resnet50_224x224 | Provides an untrained ResNet50 model that can identify 50 classes. | 1.11+ |
simpnet_cifar10 | Provides the SimpNet model checkpoint that has been pre-trained on the CIFAR10 dataset. This is part of the simpnet_tutorial. | 1.11+ |
ssd_fpn_resnet50_16x512x512 | Provides an untrained SSD-FPN (ResNet50) model, appropriate for use with the VOC 2007/2012 object detection dataset (voc0712_tfrecords). | 1.11+ |
ssdlite_mobilenet_widerface | An example ssdlite_mobilenet model that is suitable for training to the widerface dataset. | 1.13+ |
yolov3_16x416x416 | Provides a pre-trained YOLOv3 model. It requires input batch size 16 and input image 416x416x3. It is also compatible with VOC0712 data. | 1.12+ |