Structure of the code:
Code Related to Yolo:
- backbone.py: This file contains the code to build Resnet Backbone for Yolo.
- createValDataset.py: This file contains the code to Split train.csv into train and val sets.
- dataset.py: Contains the code to pack the data into pytorch Dataset to make it suitable for dataloader.
- loss.py: Contains the code for loss function of yolo.
- model.py: Contains the code to build YoloV1 model.
- train.py: Contains the code to train the model.
- utils.py: Contains all the helper functions used in the codebase.
Instructions to execute:
- Create a python environment and install pyTorch and other required libraries.
- Obtain the Voc dataset from Kaggle.
- run Python createValDataset.py in terminal
- run python train.py to train and get metrics of model.
Code Related to Detr:
- main.py: Heart of the system which binds all the things together.
- model1.py: Builds the Detr model.
- utils1.py: Contains all the helper functions for the system.
- evaluate.py: Contains the code for evaluating the model.
- run python main.py to to perform visualizations of results and get metrics and pass 1 and the true_boxes as cmd arguements.
Acknowlegements:
- Youtube of Alladion Person and Yannic Kilcher were very helpful in doing our project.
Link to PPT: https://drive.google.com/drive/folders/1wZVRThEGT-Pw4T9fpPMm74m9XFDJQUsc?usp=drive_link Link to presentation: https://drive.google.com/drive/folders/1wZVRThEGT-Pw4T9fpPMm74m9XFDJQUsc?usp=drive_link