Update README.md

README.md

@@ -9,7 +9,7 @@ pipeline_tag: object-detection
 
 # 3D Failures detection model based on Yolov5
 
-This model was created using ```YOLOv5``` in ultralytics Hub with the ```'Javiai/Javiai/failures-3D-print'```dataset.
+This model was created using ```YOLOv5``` in ultralytics Hub with the [```'Javiai/failures-3D-print'```](https://huggingface.co/datasets/Javiai/failures-3D-print) dataset.
 
 The idea is detect some failures in a 3D printing process. This model detect the part that is been printing, the extrusor, some errors and if
 there is a spaghetti error type
@@ -38,8 +38,8 @@ model = torch.hub.load('Ultralytics/yolov5', 'custom', model_path, verbose = Fal
 ### Prepare an image
 
 #### From the original dataset
-```python
 
+```python
 from datasets import load_dataset
 
 dataset = load_dataset('Javiai/failures-3D-print')
@@ -50,7 +50,6 @@ image = dataset["train"][0]["image"]
 #### From local
 
 ```python
-
 from PIL import Image
 
 image = Image.load("path/to/image")
@@ -60,7 +59,6 @@ image = Image.load("path/to/image")
 ### Inference and show the detection
 
 ```python
-
 from PIL import ImageDraw
 
 draw = ImageDraw.Draw(image)
@@ -87,5 +85,9 @@ image
 
 ```
 
+
+
+## Example image
+
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63c9c08a5fdc575773c7549b/3ZSkBvN0o8sSpQjGxdwJx.png)