Welcome to CluelessCoders’ GitHub repository on Auto-WCEBleedGen Challenge MISAHUB 2023! This repository contains code, datasets, and a stored model for the image classification as bleeding or non-bleeding. We also have an Excel sheet containing the image IDs and predicted class labels for testing datasets 1 and 2.
Finalised ColabNotebook is MisaHubResNet_FINAL.ipynb
Achieved evaluation metrics of the validation dataset.
Classification -
| Parameter | Score |
|---|---|
| Accuracy | 0.99 |
| Recall | 0.99 |
| F1 - Score | 0.99 |
Detection -
| Parameter | Score |
|---|---|
| Mean average precision | 0.58 |
| Intersection over union (IoU) (AVERAGE) | 0.44 |
| Average precision | - |
Screenshot of the best 5 predicted frames with bounding boxes and confidence level from DATASET 1 (including the CI in the screenshot itself)-
Screenshot of the best 5 predicted frames with bounding boxes and confidence level from DATASET 2 (including the CI in the screenshot itself)-
Stored Model drive link with access : https://drive.google.com/drive/folders/1s5poG5v3myJqoR2GBYZwbCbMeDJ9wSSu?usp=sharing
resnet_model_MISAHUB for classification
best.pt for yolov5