Object detection using MobileNetV3 can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, and mask image analysis.
The main process is:
Annotate images -> Generate files needed for training -> Training -> Inference
Open the webpage for image annotation.
--port 8801 is the port used by the webpage. If the port is occupied by the user, please change another port value by yourself.
The path file that generates the training image after running is one of the files needed for training.
The path file that generates the verification image after running is one of the files required for training.
Generate label category name file, which is one of the files required for training.
The category name file comes from image_annotation_classes.txt in data/train/annottions.
Delete the log file folder.
Before using tensorboard, close the old tensorboard first.
Open tensorboard to check the training status.
Inferring a single image.
Infer all images in the folder.
Infer all images in the folder, and judge whether it is overkill or underkill based on the file name.
This SDK is built in AppForAI - AI Dev Tools.
Purchase license separately: USD 600, permanent authorization, single APP authorization, single machine authorization, one-year activation, one-year download, one-year update, one-year email technical support.
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