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NVIDIA TAO Toolkit v30.2205
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NVIDIA TAO
NVIDIA TAO Toolkit v30.2205
Object Detection
Object Detection
DetectNet_v2
Data Input for Object Detection
Pre-processing the Dataset
Creating a Configuration File
Training the Model
Evaluating the Model
Using Inference on the Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to Deepstream
FasterRCNN
Preparing the Input Data Structure
Creating a Configuration File
Training the model
Evaluating the model
Running inference on the model
Pruning the model
Retraining the pruned model
Exporting the model
Deploying to DeepStream
YOLOv3
Preparing the Input Data Structure
Creating a Configuration File
Generate the Anchor Shape
Training the Model
Evaluating the Model
Running Inference on a YOLOv3 Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
YOLOv4
Preparing the Input Data Structure
Creating a Configuration File
Generate anchor shape
Training the Model
Evaluating the Model
Running Inference on a YOLOv4 Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
YOLOv4-tiny
Preparing the Input Data Structure
Creating a Configuration File
Generate anchor shape
Training the Model
Evaluating the Model
Running Inference on a YOLOv4-tiny Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
SSD
Data Input for Object Detection
Pre-processing the Dataset
Creating a Configuration File
Training the Model
Evaluating the Model
Running Inference on the Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
DSSD
Data Input for Object Detection
Pre-processing the Dataset
Creating a Configuration File
Training the Model
Evaluating the Model
Running Inference on the Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
RetinaNet
Data Input for Object Detection
Pre-processing the Dataset
Creating a Configuration File
Training the Model
Evaluating the Model
Running Inference on a RetinaNet Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
EfficientDet
Data Input for EfficientDet
Pre-processing the Dataset
Creating a Configuration File
Training the Model
Evaluating the Model
Running Inference with an EfficientDet Model
Pruning the Model
Re-training the Pruned Model
Exporting the Model
Deploying to DeepStream
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Last updated on Dec 13, 2022.
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