Mine electronic seal uses AI image intelligent video recognition and other technologies through the yolov8 network model, and the mine electronic seal yolov8 network model intelligently analyzes abnormal conditions, including but not limited to changes in the number of people, personnel entering and exiting the well, and related on-site equipment for automatic all-weather remote monitoring. YOLOv8 mainly refers to the related designs of recent algorithms such as YOLOX, YOLOv6, YOLOv7 and PPYOLOE. There are not many innovations in itself, and it is biased towards engineering practice. The main promotion is the ultralytics framework itself. According to the five parts of model structure design, Loss calculation, training data enhancement, training strategy and model reasoning process, various improvements of YOLOv8 target detection are introduced in detail , and the instance segmentation part will not be described temporarily.
The core features and changes of the YOLOv8 algorithm can be summarized as follows:
Provides a brand new SOTA model, including P5 640 and P6 1280 resolution target detection network and YOLACT-based instance segmentation model. Like YOLOv5, different size models of N/S/M/L/X scales are also provided based on the scaling factor to meet the needs of different scenarios
Backbone:
The backbone network and Neck part may refer to the design idea of YOLOv7 ELAN. The C3 structure of YOLOv5 is replaced by the C2f structure with richer gradient flow, and different channel numbers are adjusted for different scale models.
Head: Compared with yolov5, the Head part has two major improvements: 1) It is replaced with the current mainstream decoupled head structure (Decoupled-Head), which separates the classification and detection heads. 2) At the same time, it is also changed from Anchor-Based to Anchor- Free
Loss: 1) YOLOv8 abandoned the previous IOU matching or unilateral ratio distribution method, but used the Task-Aligned Assigner positive and negative sample matching method. 2) and introduced Distribution Focal Loss (DFL)
Train: The data enhancement part of the training introduces the last 10 epoch in YOLOX to turn off the Mosiac enhancement operation, which can effectively improve the accuracy
The Adapter interface defines the following methods:
public abstract void registerDataSetObserver (DataSetObserver observer)
Adapter represents a data source. This data source may change, such as adding data, deleting data, and modifying data. When the data changes, it must notify the corresponding AdapterView to make corresponding changes. In order to realize this function, the Adapter uses the observer mode. The Adapter itself is equivalent to the observed object, and the AdapterView is equivalent to the observer. Register the observer for the Adapter by calling the registerDataSetObserver method.
public abstract void unregisterDataSetObserver (DataSetObserver observer)
Unregister the observer by calling the unregisterDataSetObserver method.
public abstract int getCount () returns the number of data in the Adapter.
public abstract Object getItem (int position)
The data in the Adapter is similar to an array, and each item in it corresponds to a piece of data, and each piece of data has an index position, that is, position, and the corresponding data item in the Adapter can be obtained according to the position.
public abstract long getItemId (int position)
Get the id of the specified position data item, usually the position will be used as the id. In Adapter, relatively speaking, position is used more frequently than id.
public abstract boolean hasStableIds ()
hasStableIds indicates whether the id of the original data item will change when the data source changes. If it returns true, it means the Id remains unchanged, and if it returns false, it means it may change. The hasStableIds method of Adapter subclasses (including direct subclasses and indirect subclasses) provided by Android all return false.
public abstract View getView (int position, View convertView, ViewGroup parent)
getView is a very important method in Adapter, which will create corresponding UI items for AdapterView according to the index of the data item.