Update README.md

README.md

@@ -14,12 +14,14 @@ COHI-O365 is a real-world dataset containing 1,000 fisheye images of 74 classes,
 RMFV365 is a synthetic fisheye dataset created by applying non-linear mapping to the Objects365 dataset.  It comprises 5.1 million images offering a diverse range of perspectives and distortions, useful for training robust object detection models.
 
 
-<img src="https://github.com/IS2AI/COHI-O365/blob/main/pictures/COHI-365 Sample Images.png" width="750">
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67056b2e6409e548690b1b6f/3v4VU8qDxSczHCFHIz9bj.png)
 
 *COHI-O365 Sample Images*
 
 
-<img src="https://github.com/IS2AI/COHI-O365/blob/main/pictures/RMFV365 Sample Images.png" width="750">
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67056b2e6409e548690b1b6f/Sww7NkXYVnEiXgc4NQyr6.png)
 
 *RMFV365 Sample Images*
 
@@ -33,7 +35,8 @@ Three YOLOv7 models were trained and evaluated:
 * **YOLOv7-T2:** Trained on RMFV365.
 
 
-<img src="https://github.com/IS2AI/COHI-O365/blob/main/pictures/training_scheme.jpg" width="500">
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67056b2e6409e548690b1b6f/JMJCqaGedoORAURGclSgP.png)
 
 *Model Training Scheme*
 
@@ -143,6 +146,3 @@ The models' performance, measured by mAP<sub>50</sub>, is summarized below:
 **Table:** Objects Recognition Results on Objects365, RMFV365-v1, RMFV365, and COHI-365 Testing Sets
 
 
-## Citation
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-*(Citation information not provided in the source content)*