Added YOLOv8 example in English and other related changes

examples/yolov8/README.md

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+# Object Detection with YOLOv8
+
+Detect objects in images using the state-of-the-art YOLOv8 model.
+
+## About YOLO
+
+This node utilizes the YOLOv8 (You Only Look Once version 8) model to detect objects within images. YOLOv8 is a cutting-edge, real-time object detection system known for its speed and accuracy, capable of identifying thousands of object categories efficiently.
+
+## About YOLOV8 Service in OSCAR
+
+This service uses the pre-trained YOLOv8 model provided by DEEP-Hybrid-DataCloud for object detection. It is designed to handle synchronous invocations and real-time image processing with high scalability, managed automatically by an elastic Kubernetes cluster.
+
+In order to invoke the function, first you have to create a service, either by the OSCAR UI or by using the FDL within the following command.
+
+
+``` sh
+oscar-cli apply yolov8.yaml
+```
+
+Once the service is created you can make the invocation with the following
+command, which will store the output on a minio bucket.
+
+``` sh
+oscar-cli service put-file yolov8.yaml minio img/cat.jpg yolov8/input/cat.jpg

examples/yolov8/img/cat.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+ReferrerUrl=https://www.google.com/
+HostUrl=https://upload.wikimedia.org/wikipedia/commons/thumb/4/4d/Cat_November_2010-1a.jpg/220px-Cat_November_2010-1a.jpg

examples/yolov8/script.sh

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+#!/bin/bash
+
+IMAGE_NAME=`basename "$INPUT_FILE_PATH"`
+OUTPUT_FILE="$TMP_OUTPUT_DIR/output.png"
+
+deepaas-cli --deepaas_method_output="$OUTPUT_FILE" predict --files "$INPUT_FILE_PATH" --accept image/png 2>&1
+
+echo "Prediction was saved in: $OUTPUT_FILE"

examples/yolov8/yolov8.yaml

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+functions:
+  oscar:
+  - oscar-cluster:
+     name: yolov8
+     memory: 4Gi
+     cpu: '2.0'
+     image: ai4oshub/ai4os-yolov8-torch:latest
+     script: script.sh
+     vo: vo.imagine-ai.eu
+     allowed_users: []
+     log_level: CRITICAL		
+     input:
+     - storage_provider: minio.default
+       path: yolov8/input
+     output:
+     - storage_provider: minio.default
+       path: yolov8/output