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New img for yolov5 research

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LJ5O
2025-04-28 17:39:27 +02:00
parent 77a384f647
commit 1384f8b4bd
3 changed files with 9 additions and 2 deletions
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src/assets/img/projects/yolov5_test.png Normal file
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4
src/assets/localization/en/localization.json
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@@ -120,7 +120,7 @@
},
"semantic": {
"title": "Semantic Segmentation models study",
"text": "I installed three models on my laptop, Unet, Segnet and DeeplabV3, and trained them using the \"oxford_iiit_pet\" dataset ( from which the pictures on this page come from ). I searched about them and obtained various statistics and results, that I analysed and used to determine which one was the best Semantic Segmentation model back then.",
"text": "I installed three models on my laptop, Unet, Segnet and DeeplabV3, and trained them using the \"oxford_iiit_pet\" dataset ( from which the cat picture on this page comes from ). I searched about them and obtained various statistics and results, that I analysed and used to determine which one was the best Semantic Segmentation model back then.",
"table": {
"model": "Model",
"accuracy": "Accuracy",
@@ -132,7 +132,7 @@
},
"human_recognition": {
"title": "Human detection",
"text": "Along with the Semantic Segmentation, I was asked to find a way to recognize an human from a webcam stream. I chose the model YoloV5 to implement this functionality, and got some nice results."
"text": "Alongside with the Semantic Segmentation, I was asked to find a way to recognize an human from a webcam stream. I chose the model YoloV5 to implement this functionality, and got some nice results."
}
}
}

7
src/views/projects/semanticSegmentationView.vue
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@@ -54,6 +54,7 @@
<h2>{{ $t("projects.semantic_segmentation.content.human_recognition.title") }}</h2>
<p>{{ $t("projects.semantic_segmentation.content.human_recognition.text") }}</p>
<img :src="yolov5TestImg" id="yolo_img"/>
</article>
</template>
@@ -63,6 +64,7 @@
import semanticSegmentationCover from "@/assets/img/semantic_segmentation.png";
import hachinoheKosenImg from "@/assets/img/projects/hachinohe_kosen.png";
import yolov5TestImg from "@/assets/img/projects/yolov5_test.png";
</script>
<style scoped>
@@ -113,5 +115,10 @@
table{
margin: auto;
}
#yolo_img{
width: 80%;
max-width: 600px;
}
</style>