MMPretrain

MMPretrain

Tutorials

Google Colaboratory - Image Classification with Pretrained ResNet18 on Version 1.2.0
https://colab.research.google.com/drive/1igoW8ryWYXDkcAExicaciFvHHFbscHDa

Google Colaboratory - Custom Dataset Training with ResNet18 on Version 1.2.0
https://colab.research.google.com/drive/1RkrPGyAcS0c6CH3eC07EKKwYrzm7ovlX

Custom Dataset

ml_dataset_binimage_mmpretrain.tar.gz

Getting Started

See MMDetection also for tricks and traps

Troubleshooting - GradCAM Compatibility

https://github.com/open-mmlab/mmyolo/issues/1013

python mmpretrain/tools/visualization/vis_cam.py ...
## TypeError: forward() got an unexpected keyword argument 'use_cuda'

The latest version of grad-cam 1.5.2 is not compatible by missing the 'use_cuda' argument (Confirmed 2024/07/11)
Installing version 1.3.6 as follows fixes this problem

pip install 'grad-cam==1.3.6'

Troubleshooting - CustomDataset KeyError

https://github.com/open-mmlab/mmpretrain/issues/101

python mmpretrain/tools/train.py ...
## KeyError: 'img'

dict(type='LoadImageFromFile') is necessary in pipelines if loading image data from not pickle but image files

Troubleshooting - Missing Task Definition on Inferencer

https://mmpretrain.readthedocs.io/en/stable/_modules/mmpretrain/apis/model.html#inference_model

model = get_model(config_file, pretrained=checkpoint_file, device=device)
result = inference_model(model, img)
## No available inferencer for the model

metainfo.results.result.tasks needs to be defined in the model to use inference_model()
The following alternative approach is available for e.g., Image Classification

from mmpretrain.apis import ImageClassificationInferencer
inferencer = ImageClassificationInferencer(config_file, pretrained=checkpoint_file, device=device)
result = inferencer(img)