xref: /OK3568_Linux_fs/external/rknn-toolkit2/examples/readme.txt (revision 4882a59341e53eb6f0b4789bf948001014eff981)
1The directory structure of examples is as follows:
2.
3├── caffe
4│   ├── mobilenet_v2                    # mobilenet_v2 float model
5│   └── vgg-ssd                         # vgg-ssd float model
6├── onnx
7│   ├── resnet50v2                      # resnet50v2 float model
8│   └── yolov5                          # yolov5 float model
9├── pytorch
10│   ├── resnet18                        # resnet18 float model
11│   ├── resnet18_qat                    # resnet18 QAT model
12│   └── resnet18_export_onnx            # how to export onnx model from pytorch
13├── tensorflow
14│   ├── ssd_mobilenet_v1                # ssd_mobilenet_v1 float model
15│   └── inception_v3_qat                # inception_v3 QAT model
16├── tflite
17│   ├── mobilenet_v1                    # mobilenet_v1 float model
18│   └── mobilenet_v1_qat                # mobilenet_v1 QAT model
19├── darknet
20│   └── yolov3_416x416                  # yolov3 float model
21└── functions
22    ├── accuracy_analysis               # how to use accuracy-analysis function
23    ├── batch_size                      # how to expand batch for use multi-batch function
24    ├── multi_input_test                # multi-input float model
25    ├── hybrid_quant                    # how to use hybrid-quantization function
26    ├── mmse                            # how to use mmse function
27    ├── model_pruning                   # how to use model_pruning function
28    ├── dynamic_input                   # how to use dynamic_input function
29    └── board_test                      # how to connect the board for debugging
30