Update README.md

README.md

@@ -1,5 +1,4 @@
 ---
-license: mit
 tags:
 - YOLOv5
 - Object-Detection
@@ -15,6 +14,7 @@ It was introduced in the paper **"Unveiling the Power of Integration: Block Diag
 This model is trained using an object detection model based on YOLOv5, which offers essential capabilities for detecting various objects in an image. Using the CBD, FCA, and FCB dataset, which includes annotations for different shapes and arrows in a diagram, we train the model to recognize six labels: arrow, terminator, process, decision, data, and text.
 
 ## Training dataset
+
 - YOLOv5 is fine-tuned with the annotations provided in this [GitHub](https://github.com/shreyanshu09/Block-Diagram-Datasets) repository for symbol detection in block diagrams.
 - 396 samples from real-world English block diagram dataset (CBD)
 - 357 samples from handwritten English block diagram dataset (FC_A)
@@ -30,9 +30,6 @@ import os
 from pathlib import Path
 import torch
 
-import sys
-sys.path.append('symbol_detection/yolov5')
-
 from models.common import DetectMultiBackend
 from utils.dataloaders import IMG_FORMATS, VID_FORMATS, LoadImages, LoadScreenshots, LoadStreams
 from utils.general import LOGGER, Profile, check_file, check_img_size, check_imshow, check_requirements, colorstr, cv2, increment_path, non_max_suppression, print_args, scale_boxes, strip_optimizer, xyxy2xywh
@@ -112,9 +109,9 @@ def run_single_image_inference(model, img_path, stride, names, pt, conf_thres=0.
 
 
 # Weight path
-object_detection_output_path = 'symbol_detection/yolov5/runs/detect/exp/labels'
-yolo_weights_path = 'symbol_detection/yolov5/runs/train/best_all/weights/best.pt'
-yolo_yaml_file = 'symbol_detection/yolov5/data/mydata.yaml'
+object_detection_output_path = 'symbol_detection/runs/detect/exp/labels'
+yolo_weights_path = 'symbol_detection/runs/train/best_all/weights/best.pt'
+yolo_yaml_file = 'symbol_detection/data/mydata.yaml'
 
 yolo_model = load_model(yolo_weights_path, device='cuda:0', dnn=False, data=yolo_yaml_file, fp16=False)
 stride, names, pt = yolo_model.stride, yolo_model.names, yolo_model.pt
@@ -125,4 +122,9 @@ labels = run_single_image_inference(yolo_model, image_path, stride, names, pt)
 ```
 
 ## Contact
+
 If you have any questions about this work, please contact **[Shreyanshu Bhushan](https://github.com/shreyanshu09)** using the following email addresses: **shreyanshubhushan@gmail.com**.
+
+## License
+
+The content of this project itself is licensed under the [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/).