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template.yaml
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template.yaml
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name: text-spotting-0005
domain: Text Spotting
problem: Alphanumeric Text Spotting
framework: OTEDetection v2.9.1
summary: Text spotting model based on Mask-RCNN with text recognition head.
annotation_format: COCO with text
initial_weights: snapshot.pth
dependencies:
- sha256: 30e6918e8402c23bb89300807c83870e913581ffdc5102a3399b6bbe80c92e7e
size: 223291625
source: https://storage.openvinotoolkit.org/repositories/openvino_training_extensions/models/text_spotting/alphanumeric_text_spotting/text_spotting_0005/epoch_25.pth
destination: snapshot.pth
- source: ../../../../../ote/tools/train.py
destination: train.py
- source: ../../../../../ote/tools/eval.py
destination: eval.py
- source: ../../../../../ote/tools/export.py
destination: export.py
- source: ../../../../../ote/tools/compress.py
destination: compress.py
- source: ../../../../../ote
destination: packages/ote
- source: ../../requirements.txt
destination: requirements.txt
max_nodes: 1
training_target:
- GPU
inference_target:
- CPU
hyper_parameters:
basic:
batch_size: 2
base_learning_rate: 0.02
epochs: 25
output_format:
onnx:
default: true
openvino:
default: true
input_format: BGR
optimisations: ~
metrics:
- display_name: Size
key: size
unit: Mp
value: 27.76
- display_name: Complexity
key: complexity
unit: GFLOPs
value: 190.5
- display_name: F1-score
key: f1
unit: '%'
value: 88.87
- display_name: Word Spotting (N)
key: word_spotting
unit: '%'
value: 71.29
- display_name: End-to-End recognition (N)
key: e2e_recognition
unit: '%'
value: 68.55
gpu_num: 4
tensorboard: true
config: model.py