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Akriel/
ResNetYoloV1

tensorboard

computer_vision

vision_models_playground

custom-implementation

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Vision Models Playground

This is a trained model from the Vision Models Playground repository. Link to the repository: https://github.com/Akrielz/vision_models_playground

Model

This model is a custom implementation of ResNetYoloV1 from the vision_models_playground.models.segmentation.yolo_v1 module. Please look in the config file for more information about the model architecture.

Usage

To load the torch model, you can use the following code snippet:

python

import torch
from vision_models_playground.utility.hub import load_vmp_model_from_hub


model = load_vmp_model_from_hub("Akriel/ResNetYoloV1")

x = torch.randn(...)
y = model(x)  # y will be of type torch.Tensor

To load the pipeline that includes the model, you can use the following code snippet:

python

from vision_models_playground.utility.hub import load_vmp_pipeline_from_hub

pipeline = load_vmp_pipeline_from_hub("Akriel/ResNetYoloV1")

x = raw_data  # raw_data will be of type pipeline.input_type
y = pipeline(x)  # y will be of type pipeline.output_type

Metrics

The model was evaluated on the following dataset: YoloPascalVocDataset from vision_models_playground.datasets.yolo_pascal_voc_dataset

These are the results of the evaluation:

MulticlassAccuracy: 0.7241
MulticlassAveragePrecision: 0.7643
MulticlassAUROC: 0.9684
Dice: 0.7241
MulticlassF1Score: 0.7241
LossTracker: 4.1958

Additional Information

The train and evaluation runs are also saved using tensorboard. You can use the following command to visualize the runs:

tensorboard --logdir ./model

tensorboard --logdir ./eval