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:
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:
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