2022.03.05
文章目录使用TensorFlow Lite 部署自定义对象检测模型[1]
一.訓練自定義模型[4]
1.收集數據2.訓練模型 二.集成TFLite模型的步驟
一.訓練自定義模型[4]步驟:
1.收集數據打標籤—標註精靈
2.訓練模型 二.集成TFLite模型的步驟三.代碼實現:(教程)[1]
下載源代碼
odml-pathways-main.zipodml-pathways-mainobject-detectioncodelab2android
starter – 核心關鍵代碼沒寫
final – 完整可運行的
引用:
[1] 使用 TensorFlow Lite 构建和部署自定义对象检测模(Android)
[2] 視頻講解參考
[3] TensorFlow Hub
[4] Train a salad detector with TFLite Model Maker
[5] Build and deploy custom object detection model with TensorFlow Lite|Workshop https://wwwyoutubecom/watch?v=vLxn5mOuWAk
[6] EfficientDet:Towards Scalable and Efficient Object Detection
https://aigoogleblogcom/2020/04/efficientdet-towards-scalable-andhtml
[7] WhatObjectCategories/Labels Are In COCO Dataset?https//techamikelive.com/node718/what-object-categories-labels-are-in-coco-dataset/
[8] MicrosoftCOCO:CommonObiectsinContexthttps://arxivorg/pdf/14050312pdf
[9] 目标检测中的AP，mAPhttps//zhuanlanzhihucom/p/888968686用YOLOv5+DeepSORT，打造实时多目标跟踪模型 https://mp.weixinqqcom/s/diPOaolDEf78t4AeU-i5bw
