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Merge pull request #266 from Dialdroid/dev-dieagra
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Added YOLOv8 example in English and other related changes
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Dialdroid authored Oct 21, 2024
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24 changes: 24 additions & 0 deletions 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
Binary file added examples/yolov8/img/cat.jpg
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4 changes: 4 additions & 0 deletions 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
8 changes: 8 additions & 0 deletions 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"
17 changes: 17 additions & 0 deletions 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

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