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Object Detection
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NVIDIA TAO
NVIDIA TAO Toolkit v3.0
Object Detection
NVIDIA TAO Release tlt.30
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 an experiment spec file - Specification file for FasterRCNN
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
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
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
SSD
Data Input for Object Detection
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
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
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
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Last updated on Jul 28, 2021.
