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New img for yolov5 research
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@@ -120,7 +120,7 @@
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},
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"semantic": {
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"title": "Semantic Segmentation models study",
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"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.",
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"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.",
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"table": {
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"model": "Model",
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"accuracy": "Accuracy",
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@@ -132,7 +132,7 @@
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},
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"human_recognition": {
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"title": "Human detection",
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"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."
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"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."
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}
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}
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}
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