Adding usage on README

README.md

@@ -23,31 +23,18 @@ Ensure you have Python 3.6 or later installed. Then install the required package
 pip install transformers torch torchvision
 ```
 
-### Inference
+### How to use
 
-You can perform inference with the following code snippet:
+You can do the predictions with the following code snippet:
 ```
-from transformers import Yolov5Model, Yolov5FeatureExtractor
+import ultralytics
+from ultralytics import YOLO
 
-# Load model and feature extractor
-model_id = "armvectores/yolov5_handwritten_text_detection"
-feature_extractor = Yolov5FeatureExtractor.from_pretrained(model_id)
-model = Yolov5Model.from_pretrained(model_id)
+# Load weights for YOLO
+model = YOLO('best.pt')
 
-# Prepare your image (replace 'path/to/your/image.jpg' with your actual image path)
-image = Image.open('path/to/your/image.jpg')
-
-# Perform inference
-inputs = feature_extractor(images=image, return_tensors="pt")
-outputs = model(**inputs)
-
-# Analyze the outputs
-detections = outputs[0]
-
-# detections consist of [x_min, y_min, x_max, y_max, confidence, class]
-# Loop through detections and print results
-for detection in detections:
-    print(f"Coordinates: {detection[:4]}, Confidence: {detection[4]}")
+# Do the predictions
+model.predict(source="path_to_your_image", save=True, show=True, show_labels=False, show_conf=False, conf=0.3)
 ```
 
 ## Limitations
@@ -66,4 +53,14 @@ This description should provide users with an overview of the YOLOv5 model tailo
 
 <p align="center">
  <img width="200px" src="results.png" alt="qr"/>
+</p>
+
+## Tests
+
+<p align="center">
+ <img width="400px" src="prediction1.png" alt="qr"/>
+</p>
+
+<p align="center">
+ <img width="400px" src="prediction2.png" alt="qr"/>
 </p>