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Merge pull request #266 from Dialdroid/dev-dieagra
Added YOLOv8 example in English and other related changes
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# Object Detection with YOLOv8 | ||
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Detect objects in images using the state-of-the-art YOLOv8 model. | ||
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## About YOLO | ||
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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. | ||
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## About YOLOV8 Service in OSCAR | ||
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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. | ||
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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. | ||
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``` sh | ||
oscar-cli apply yolov8.yaml | ||
``` | ||
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Once the service is created you can make the invocation with the following | ||
command, which will store the output on a minio bucket. | ||
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``` sh | ||
oscar-cli service put-file yolov8.yaml minio img/cat.jpg yolov8/input/cat.jpg |
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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 |
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#!/bin/bash | ||
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IMAGE_NAME=`basename "$INPUT_FILE_PATH"` | ||
OUTPUT_FILE="$TMP_OUTPUT_DIR/output.png" | ||
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deepaas-cli --deepaas_method_output="$OUTPUT_FILE" predict --files "$INPUT_FILE_PATH" --accept image/png 2>&1 | ||
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echo "Prediction was saved in: $OUTPUT_FILE" |
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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 |