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
  • TensorRT Engine Generation, Validation, and INT8 Calibration
  • 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
  • TensorRT engine generation, validation, and int8 calibration
• 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
  • TensorRT engine generation, validation, and int8 calibration
  • 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
  • TensorRT engine generation, validation, and int8 calibration
  • 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
  • TensorRT engine generation, validation, and int8 calibration
  • 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
  • TensorRT engine generation, validation, and int8 calibration
  • 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
  • TensorRT engine generation, validation, and int8 calibration
  • 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
  • TensorRT Engine Generation, Validation, and int8 Calibration
  • Deploying to DeepStream
• EfficientDet (TF1)
  • 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
  • TensorRT Engine Generation, Validation, and int8 Calibration
  • Deploying to DeepStream