Dataset Preparation The base data directory should consist of the following files: "images" folder - containing the images for train, test and val "labels" folder - containing the labels for train, test and val in .txt yolo format. Each image has seperate file.

	"class.txt" - Txt file with class names (Input to the conv_xml_to_txt.py file)

	Running conv_xml_to_txt.py at the base data directory:
	"train/txt" - generate txt files containing labels(class,xyxy) from original xml labels(Input)
	"val/txt" - generate txt files containing labels(class,xyxy) from original xml labels(Input)
	"train/txt" - generate txt files containing labels(class,xyxy) from original xml labels(Input)

Generated custom dataset should be in the format :

custom_dataset
├── images
│   ├── train
│   │   ├── train0.jpg
│   │   └── train1.jpg
│   ├── val
│   │   ├── val0.jpg
│   │   └── val1.jpg
│   └── test
│       ├── test0.jpg
│       └── test1.jpg
└── labels
   	    ├── train
	    │   ├── train0.txt
	    │   └── train1.txt
	    ├── val
	    │   ├── val0.txt
	    │   └── val1.txt
	    └── test
    		├── test0.txt
    		└── test1.txt

TRAIN

- python train.py E:\IISc\Object_detection\YOLOv7\yolov7-main\weights\yolov7_training.pt --data E:\IISc\Object_detection\YOLOv7\yolov7-main\data\custom.yaml --workers 4 --batch-size 4 --img 640 640 --cfg E:\IISc\Object_detection\YOLOv7\yolov7-main\cfg\training\yolov7.yaml --name yolov7 --hyp E:\IISc\Object_detection\YOLOv7\yolov7-main\data\hyp.scratch.p5.yaml

saved weights
- runs\train\yolov7\weights

(NOTE: DELETE the train.cache, val.cache, test.cache files generated in main_dataset\labels after each run)

Evaluate : (For final mAP calculation on custom dataset with xywh labels)

Set val variable value in data\custom.yaml as- 
E:\\IISc\\Object_detection\\IDD\\backup\\images\\test	

- python test.py --data E:\IISc\Object_detection\YOLOv7\yolov7-main\data\custom.yaml --img 640 --batch 2 --conf 0.001 --iou 0.65 --device 0 --weights E:\IISc\Object_detection\YOLOv7\yolov7-main\weights\yolov7_training.pt --name yolov7_640_val

(NOTE: DELETE the train.cache, val.cache, test.cache files generated in main_dataset\labels after each run)

EVALUATION : (Use xyxy format labels for label and image paths in main() of Evaluation.py) - python Evaluation.py - Generate csv files with results in output_files (Refer Readme_evaluation.txt for details)

(NOTE: DELETE the train.cache, val.cache, test.cache files generated in main_dataset\labels after each run)