README with ToDos implemented
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@ -50,7 +50,6 @@ im2 = ImageOps.grayscale(im1)
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* check other pretrained models from torchvision.models.detection, e.g. fasterrcnn_resnet50_fpn_v2
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## config.py
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Containes Hyperparameters used by the scripts.
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## ToDos:
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@ -60,6 +59,8 @@ Containes Hyperparameters used by the scripts.
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Classes and functions to save models and store loss values for later illustration.
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Also includes helper functions...
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## ToDos:
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### train.py
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Code training the model using the stored images in ./data/dataset and the .csv files
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containing the bounding boxes meant for training. For each epoch test-loss (without
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@ -68,9 +69,13 @@ of the previous epochs. If the new model is the best model, the model.state_dict
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./model_outputs as best_model.pth.
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## ToDos:
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*
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### inference.py
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Currently, this code performs predictions based in the test dataset (img and corresponding csv file).
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However, this code shall be used to infer totally unknown images. Prediction results are ilustrated
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and stored in ./inference_output
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## ToDo:
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* implement path where no csv file is needed...
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