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template.yaml
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template.yaml
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name: s3d-rgb-mobilenet-v3-stream-jester
domain: Action Recognition 2
problem: Gesture Recognition
framework: OTEAction v0.6.0
summary: ASL Recognition based on S3D-MobileNet-V3.
annotation_format: CustomAction
initial_weights: snapshot.pth
dependencies:
- sha256: 387f42e4a71ca0955e174d4661f795989b35056993f0049f45df4c56f83273d4
size: 33272762
source: https://docs.google.com/uc?export=download&id=1lDm2qOxMRyXZW6y7owlQBv8SGvGIKpcX
destination: snapshot.pth
- source: ../../../../../pytorch_toolkit/ote/tools/train.py
destination: train.py
- source: ../../../../../pytorch_toolkit/ote/tools/eval.py
destination: eval.py
- source: ../../../../../pytorch_toolkit/ote/tools/export.py
destination: export.py
- source: ../../../../../pytorch_toolkit/ote/tools/compress.py
destination: compress.py
- source: ../../../../../pytorch_toolkit/ote
destination: packages/ote
- source: ../../requirements.txt
destination: requirements.txt
max_nodes: 1
training_target:
- GPU
inference_target:
- CPU
- iGPU
hyper_parameters:
basic:
batch_size: 14
base_learning_rate: 0.01
epochs: 65
output_format:
onnx:
default: true
openvino:
default: true
input_format: RGB
optimisations: ~
metrics:
- display_name: Size
key: size
unit: Mp
value: 4.133
- display_name: Complexity
key: complexity
unit: GFLOPs
value: 6.66
- display_name: Top-1 accuracy
key: accuracy
unit: '%'
value: 84.7
gpu_num: 2
tensorboard: true
config: model.py