Update README.md

README.md

@@ -2,8 +2,8 @@
 # Panoramic X-ray Tooth Dataset
 
 ## Description
-This dataset contains over 500 panoramic dental X-ray images, accompanied by segmentation masks and annotation files. The dataset aims to support dental research, machine learning model development, and automated dental diagnostics. The images in this dataset represent a variety of dental conditions and tooth structures.
-
+This dataset, curated by Humans in the Loop, features over 500 panoramic dental X-ray images, complete with segmentation masks and annotation files. Designed to support dental research, machine learning model development, and automated dental diagnostics, the dataset showcases a variety of dental conditions and tooth structures. The high-quality segmentation masks, produced through expert human annotation, enhance the precision and reliability of model training. This dataset is available on Kaggle through Humans in the Loop’s official page, reflecting their commitment to providing accurate, well-annotated data for AI applications.This dataset, curated by Humans in the Loop, features over 500 panoramic dental X-ray images, complete with segmentation masks and annotation files. Designed to support dental research, machine learning model development, and automated dental diagnostics, the dataset showcases a variety of dental conditions and tooth structures. The high-quality segmentation masks, produced through expert human annotation, enhance the precision and reliability of model training. This dataset is available on Kaggle through Humans in the Loop’s official page, reflecting their commitment to providing accurate, well-annotated data for AI applications.
+https://www.kaggle.com/datasets/humansintheloop/
 ## Dataset Structure
 The dataset includes the following components:
 
@@ -13,24 +13,21 @@ The dataset includes the following components:
 4. **JSON Annotation Files**: Each X-ray image is accompanied by a JSON file containing polygon coordinates outlining the exterior boundaries of each tooth, along with class labels.
 
 ### Example Files
-- **1.jpg**: Example panoramic X-ray image. 
-  - **Explanation**: This image is a standard panoramic X-ray, capturing the full set of teeth, jaw, and surrounding bone structure in a single image. The process involves using a rotating arm of an X-ray machine that captures the dental arch. This type of imaging is widely used for dental diagnosis, as it provides a comprehensive view of the mouth.
-  - **Usage**: This image can be used to detect dental anomalies, evaluate tooth alignment, and check for issues such as impacted teeth or bone loss.
 
-- **1.png**: Corresponding machine or human mask.
-  - **Explanation**: The mask highlights individual teeth by segmenting them from the X-ray image. In the case of machine-generated masks, computer vision models have been trained to detect and separate each tooth, while human masks are manually drawn for accuracy.
-  - **Usage**: Overlay the mask on the X-ray to visualize segmentation. This is useful for training machine learning models to improve automatic segmentation accuracy.
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/66b24a579f3dfa895ca9286d/aT6K4yq6MRQOuAXqYf3SB.jpeg)
+
+Example panoramic X-ray image.This image is a standard panoramic X-ray, capturing the full set of teeth, jaw, and surrounding bone structure in a single image. The process involves using a rotating arm of an X-ray machine that captures the dental arch. This type of imaging is widely used for dental diagnosis, as it provides a comprehensive view of the mouth.This image can be used to detect dental anomalies, evaluate tooth alignment, and check for issues such as impacted teeth or bone loss.
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/66b24a579f3dfa895ca9286d/3m_g2O9Bo7sGAwKsV0uvN.png)
 
-- **1.jpg.json**: Annotation file containing labeled polygon data for each tooth.
-  - **Explanation**: This JSON file contains detailed polygon coordinates that map out the boundaries of each tooth detected in the X-ray. Each entry in the file corresponds to a specific tooth number or region, providing crucial information for dental diagnostics and AI model training.
-  - **Usage**: The polygon data can be used to train segmentation models, fine-tune existing algorithms, or serve as ground truth for evaluating model performance.
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/66b24a579f3dfa895ca9286d/qklFYtxQXpq8jqxdcIpjC.png)
 
-## JSON File Breakdown
-Each JSON file includes:
-- **Objects**: A list of segmented teeth, each represented by a polygon.
-- **ClassTitle**: Labels representing tooth numbers.
-- **Points**: Polygon coordinates marking the exterior of each detected tooth.
-- **Size**: Width and height of the original image.
+Corresponding machine or human mask.The mask highlights individual teeth by segmenting them from the X-ray image.In the case of machine-generated masks, computer vision models have been trained to detect and separate each tooth, while human masks are manually drawn for accuracy.Overlay the mask on the X-ray to visualize segmentation. This is useful for training machine learning models to improve automatic segmentation accuracy.
+
+Annotation file containing labeled polygon data for each tooth.This JSON file contains detailed polygon coordinates that map out the boundaries of each tooth detected in the X-ray. Each entry in the file corresponds to a specific tooth number or region, providing crucial information for dental diagnostics and AI model training.The polygon data can be used to train segmentation models, fine-tune existing algorithms, or serve as ground truth for evaluating model performance.
+
+ 
 
 **Example Entry:**
 ```json
@@ -46,23 +43,6 @@ Each JSON file includes:
 ## Usage
 This dataset can be used to train segmentation models for tooth identification, dental health assessment, and automated diagnostics. The machine-generated masks can help in benchmarking, while human-annotated masks provide reliable ground truth for comparison.
 
-### Application Workflow
-1. **Load the X-ray Images**: Use the images for preprocessing and augmentation.
-2. **Apply the Masks**: Overlay machine or human masks to visualize tooth segmentation.
-3. **Model Training**: Utilize the masks and annotations to train segmentation models.
-4. **Evaluation**: Compare model output with human annotations for accuracy assessment.
-
-## Author and Attribution
-- **Annotations by**: GhazalehHITL
-- **Dataset Curator**: [Your Name or Profile Link]
-- **Source**: This dataset is publicly available for non-commercial research and development.
 
-## Download
-Click the link below to download the dataset:
-[Download Dataset](#)
 
-## License
-This dataset is licensed for educational and research purposes. Proper attribution is required for any publications or projects utilizing this dataset.
 
----
-If you have any questions or require further information, feel free to reach out via [Your Contact Information].