update 27/07/24

.gitattributes

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README.md

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----
-metrics:
-- precision
-- recall
-- mean_iou
-library_name: yolov5
-pipeline_tag: object-detection
-tags:
-- astronomy
-- space
-- yolo
-- yolov5
-- moon
-- crater/boulder detection
-- OHRC
-- ISRO
-- Chandrayaan
----
-# YOLOv5 for Crater/Boulder detection on Moon
-
-A yolov5s and a yolov5l model was trained on a labelled dataset of marked craters/boulders on moon. This was trained for the 3rd problem statement *Automatic detection of craters & boulders from Orbiter High Resolution Camera(OHRC) images using AI/ML techniques* of *Bharatiya Antariksh Hackathon 2024*.
-
-## How to use
-
-- Install [yolov5](https://github.com/fcakyon/yolov5-pip):
-
-```bash
-pip install -U yolov5
-```
-
-- Load model and perform prediction:
-
-```python
-import yolov5
-# from PIL import Image
-
-# load model
-model = yolov5.load('Gurveer05/moon-crater-boulder-detection-yolov5')
-  
-# set model parameters
-model.conf = 0.25  # NMS confidence threshold
-model.iou = 0.45  # NMS IoU threshold
-model.agnostic = False  # NMS class-agnostic
-model.multi_label = False  # NMS multiple labels per box
-model.max_det = 1000  # maximum number of detections per image
-
-# set image
-img = 'path/to/image' # or use: img = Image.open('/path/to/image')
-
-# perform inference
-results = model(img) # add size=640 if needed
-
-# inference with test time augmentation
-results = model(img, augment=True)
-
-# parse results
-predictions = results.pred[0]
-boxes = predictions[:, :4] # x1, y1, x2, y2
-scores = predictions[:, 4]
-categories = predictions[:, 5]
-
-# show detection bounding boxes on image
-results.show()
-
-# save results into "results/" folder
-results.save(save_dir='results/')
-```
-
-- Finetune the model on your custom dataset:
-
-```bash
-yolov5 train --data data.yaml --img 640 --batch 16 --weights Gurveer05/moon-crater-boulder-detection-yolov5 --epochs 10
-```
-
-## References
-
-- [Dataset](https://www.kaggle.com/datasets/gurveersinghvirk/crater-boulder-moon-yolo-format)
-- [Code for training](https://www.kaggle.com/code/gurveersinghvirk/isro-hackathon?scriptVersionId=189827639)
-- [Output for OHRC images](https://www.kaggle.com/datasets/florabert/ohrc-moon-crater-boulder-detections-yolov5)
-- [Sliced OHRC images input](https://www.kaggle.com/datasets/gurveersinghvirk/ohrc-sliced)
-- [Code for inference on sliced OHRC images (Marked Images and Bounding Boxes CSV outputs)](https://www.kaggle.com/code/florabert/isro-hackathon-copy-1?scriptVersionId=189900697)
-- [Code for inference on sliced OHRC images (lat/long .shp files for bounding boxes and center)](https://www.kaggle.com/code/florabert/isro-hackathon-copy-1?scriptVersionId=189903524)
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